Computational Biology and High Performance Computing 2000

Energy Technology Data Exchange (ETDEWEB)

Simon, Horst D.; Zorn, Manfred D.; Spengler, Sylvia J.; Shoichet, Brian K.; Stewart, Craig; Dubchak, Inna L.; Arkin, Adam P.

2000-10-19

The pace of extraordinary advances in molecular biology has accelerated in the past decade due in large part to discoveries coming from genome projects on human and model organisms. The advances in the genome project so far, happening well ahead of schedule and under budget, have exceeded any dreams by its protagonists, let alone formal expectations. Biologists expect the next phase of the genome project to be even more startling in terms of dramatic breakthroughs in our understanding of human biology, the biology of health and of disease. Only today can biologists begin to envision the necessary experimental, computational and theoretical steps necessary to exploit genome sequence information for its medical impact, its contribution to biotechnology and economic competitiveness, and its ultimate contribution to environmental quality. High performance computing has become one of the critical enabling technologies, which will help to translate this vision of future advances in biology into reality. Biologists are increasingly becoming aware of the potential of high performance computing. The goal of this tutorial is to introduce the exciting new developments in computational biology and genomics to the high performance computing community.

Computational biology

DEFF Research Database (Denmark)

Hartmann, Lars Røeboe; Jones, Neil; Simonsen, Jakob Grue

2011-01-01

Computation via biological devices has been the subject of close scrutiny since von Neumann’s early work some 60 years ago. In spite of the many relevant works in this field, the notion of programming biological devices seems to be, at best, ill-defined. While many devices are claimed or proved t...

Applicability of Computational Systems Biology in Toxicology

DEFF Research Database (Denmark)

Kongsbak, Kristine Grønning; Hadrup, Niels; Audouze, Karine Marie Laure

2014-01-01

be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method......Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources...... and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search...

Catalyzing Inquiry at the Interface of Computing and Biology

Energy Technology Data Exchange (ETDEWEB)

John Wooley; Herbert S. Lin

2005-10-30

This study is the first comprehensive NRC study that suggests a high-level intellectual structure for Federal agencies for supporting work at the biology/computing interface. The report seeks to establish the intellectual legitimacy of a fundamentally cross-disciplinary collaboration between biologists and computer scientists. That is, while some universities are increasingly favorable to research at the intersection, life science researchers at other universities are strongly impeded in their efforts to collaborate. This report addresses these impediments and describes proven strategies for overcoming them. An important feature of the report is the use of well-documented examples that describe clearly to individuals not trained in computer science the value and usage of computing across the biological sciences, from genes and proteins to networks and pathways, from organelles to cells, and from individual organisms to populations and ecosystems. It is hoped that these examples will be useful to students in the life sciences to motivate (continued) study in computer science that will enable them to be more facile users of computing in their future biological studies.

Mammalian synthetic biology for studying the cell.

Science.gov (United States)

Mathur, Melina; Xiang, Joy S; Smolke, Christina D

2017-01-02

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.

Cell illustrator 4.0: a computational platform for systems biology.

Science.gov (United States)

Nagasaki, Masao; Saito, Ayumu; Jeong, Euna; Li, Chen; Kojima, Kaname; Ikeda, Emi; Miyano, Satoru

2011-01-01

Cell Illustrator is a software platform for Systems Biology that uses the concept of Petri net for modeling and simulating biopathways. It is intended for biological scientists working at bench. The latest version of Cell Illustrator 4.0 uses Java Web Start technology and is enhanced with new capabilities, including: automatic graph grid layout algorithms using ontology information; tools using Cell System Markup Language (CSML) 3.0 and Cell System Ontology 3.0; parameter search module; high-performance simulation module; CSML database management system; conversion from CSML model to programming languages (FORTRAN, C, C++, Java, Python and Perl); import from SBML, CellML, and BioPAX; and, export to SVG and HTML. Cell Illustrator employs an extension of hybrid Petri net in an object-oriented style so that biopathway models can include objects such as DNA sequence, molecular density, 3D localization information, transcription with frame-shift, translation with codon table, as well as biochemical reactions.

Michael Levitt and Computational Biology

Science.gov (United States)

dropdown arrow Site Map A-Z Index Menu Synopsis Michael Levitt and Computational Biology Resources with Michael Levitt, PhD, professor of structural biology at the Stanford University School of Medicine, has function. ... Levitt's early work pioneered computational structural biology, which helped to predict

Applications of membrane computing in systems and synthetic biology

CERN Document Server

Gheorghe, Marian; Pérez-Jiménez, Mario

2014-01-01

Membrane Computing was introduced as a computational paradigm in Natural Computing. The models introduced, called Membrane (or P) Systems, provide a coherent platform to describe and study living cells as computational systems. Membrane Systems have been investigated for their computational aspects and employed to model problems in other fields, like: Computer Science, Linguistics, Biology, Economy, Computer Graphics, Robotics, etc. Their inherent parallelism, heterogeneity and intrinsic versatility allow them to model a broad range of processes and phenomena, being also an efficient means to solve and analyze problems in a novel way. Membrane Computing has been used to model biological systems, becoming with time a thorough modeling paradigm comparable, in its modeling and predicting capabilities, to more established models in this area. This book is the result of the need to collect, in an organic way, different facets of this paradigm. The chapters of this book, together with the web pages accompanying th...

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

Directory of Open Access Journals (Sweden)

Daniel eLewis

2014-12-01

Full Text Available As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo systems, with only a few examples of prominent work done on predicting the dynamics of cell-free systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

UC Merced Center for Computational Biology Final Report

Energy Technology Data Exchange (ETDEWEB)

Colvin, Michael; Watanabe, Masakatsu

2010-11-30

made possible by the CCB from its inception until August, 2010, at the end of the final extension. Although DOE support for the center ended in August 2010, the CCB will continue to exist and support its original objectives. The research and academic programs fostered by the CCB have led to additional extramural funding from other agencies, and we anticipate that CCB will continue to provide support for quantitative and computational biology program at UC Merced for many years to come. Since its inception in fall 2004, CCB research projects have continuously had a multi-institutional collaboration with Lawrence Livermore National Laboratory (LLNL), and the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, as well as individual collaborators at other sites. CCB affiliated faculty cover a broad range of computational and mathematical research including molecular modeling, cell biology, applied math, evolutional biology, bioinformatics, etc. The CCB sponsored the first distinguished speaker series at UC Merced, which had an important role is spreading the word about the computational biology emphasis at this new campus. One of CCB's original goals is to help train a new generation of biologists who bridge the gap between the computational and life sciences. To archive this goal, by summer 2006, a new program - summer undergraduate internship program, have been established under CCB to train the highly mathematical and computationally intensive Biological Science researchers. By the end of summer 2010, 44 undergraduate students had gone through this program. Out of those participants, 11 students have been admitted to graduate schools and 10 more students are interested in pursuing graduate studies in the sciences. The center is also continuing to facilitate the development and dissemination of undergraduate and graduate course materials based on the latest research in computational biology.

Industrial systems biology and its impact on synthetic biology of yeast cell factories

DEFF Research Database (Denmark)

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-01-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools......, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex...... regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal...

Industrial systems biology and its impact on synthetic biology of yeast cell factories.

Science.gov (United States)

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-06-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

A molecular computer to classify cells

CERN Multimedia

CERN. Geneva

2018-01-01

If only we had a small molecular computer to leverage this disparity, programmable to optimally recognize different classes of cells and, once inside a target cell, to execute an action. Like what a student team researched for this year's synthetic biology iGEM competition.

The case for biological quantum computer elements

Science.gov (United States)

Baer, Wolfgang; Pizzi, Rita

2009-05-01

An extension to vonNeumann's analysis of quantum theory suggests self-measurement is a fundamental process of Nature. By mapping the quantum computer to the brain architecture we will argue that the cognitive experience results from a measurement of a quantum memory maintained by biological entities. The insight provided by this mapping suggests quantum effects are not restricted to small atomic and nuclear phenomena but are an integral part of our own cognitive experience and further that the architecture of a quantum computer system parallels that of a conscious brain. We will then review the suggestions for biological quantum elements in basic neural structures and address the de-coherence objection by arguing for a self- measurement event model of Nature. We will argue that to first order approximation the universe is composed of isolated self-measurement events which guaranties coherence. Controlled de-coherence is treated as the input/output interactions between quantum elements of a quantum computer and the quantum memory maintained by biological entities cognizant of the quantum calculation results. Lastly we will present stem-cell based neuron experiments conducted by one of us with the aim of demonstrating the occurrence of quantum effects in living neural networks and discuss future research projects intended to reach this objective.

Interactomes to Biological Phase Space: a call to begin thinking at a new level in computational biology.

Energy Technology Data Exchange (ETDEWEB)

Davidson, George S.; Brown, William Michael

2007-09-01

Techniques for high throughput determinations of interactomes, together with high resolution protein collocalizations maps within organelles and through membranes will soon create a vast resource. With these data, biological descriptions, akin to the high dimensional phase spaces familiar to physicists, will become possible. These descriptions will capture sufficient information to make possible realistic, system-level models of cells. The descriptions and the computational models they enable will require powerful computing techniques. This report is offered as a call to the computational biology community to begin thinking at this scale and as a challenge to develop the required algorithms and codes to make use of the new data.3

Genome Annotation in a Community College Cell Biology Lab

Science.gov (United States)

Beagley, C. Timothy

2013-01-01

The Biology Department at Salt Lake Community College has used the IMG-ACT toolbox to introduce a genome mapping and annotation exercise into the laboratory portion of its Cell Biology course. This project provides students with an authentic inquiry-based learning experience while introducing them to computational biology and contemporary learning…

A first attempt to bring computational biology into advanced high school biology classrooms.

Science.gov (United States)

Gallagher, Suzanne Renick; Coon, William; Donley, Kristin; Scott, Abby; Goldberg, Debra S

2011-10-01

Computer science has become ubiquitous in many areas of biological research, yet most high school and even college students are unaware of this. As a result, many college biology majors graduate without adequate computational skills for contemporary fields of biology. The absence of a computational element in secondary school biology classrooms is of growing concern to the computational biology community and biology teachers who would like to acquaint their students with updated approaches in the discipline. We present a first attempt to correct this absence by introducing a computational biology element to teach genetic evolution into advanced biology classes in two local high schools. Our primary goal was to show students how computation is used in biology and why a basic understanding of computation is necessary for research in many fields of biology. This curriculum is intended to be taught by a computational biologist who has worked with a high school advanced biology teacher to adapt the unit for his/her classroom, but a motivated high school teacher comfortable with mathematics and computing may be able to teach this alone. In this paper, we present our curriculum, which takes into consideration the constraints of the required curriculum, and discuss our experiences teaching it. We describe the successes and challenges we encountered while bringing this unit to high school students, discuss how we addressed these challenges, and make suggestions for future versions of this curriculum.We believe that our curriculum can be a valuable seed for further development of computational activities aimed at high school biology students. Further, our experiences may be of value to others teaching computational biology at this level. Our curriculum can be obtained at http://ecsite.cs.colorado.edu/?page_id=149#biology or by contacting the authors.

Computational aspects of systematic biology.

Science.gov (United States)

Lilburn, Timothy G; Harrison, Scott H; Cole, James R; Garrity, George M

2006-06-01

We review the resources available to systematic biologists who wish to use computers to build classifications. Algorithm development is in an early stage, and only a few examples of integrated applications for systematic biology are available. The availability of data is crucial if systematic biology is to enter the computer age.

Computer support for physiological cell modelling using an ontology on cell physiology.

Science.gov (United States)

Takao, Shimayoshi; Kazuhiro, Komurasaki; Akira, Amano; Takeshi, Iwashita; Masanori, Kanazawa; Tetsuya, Matsuda

2006-01-01

The development of electrophysiological whole cell models to support the understanding of biological mechanisms is increasing rapidly. Due to the complexity of biological systems, comprehensive cell models, which are composed of many imported sub-models of functional elements, can get quite complicated as well, making computer modification difficult. Here, we propose a computer support to enhance structural changes of cell models, employing the markup languages CellML and our original PMSML (physiological model structure markup language), in addition to a new ontology for cell physiological modelling. In particular, a method to make references from CellML files to the ontology and a method to assist manipulation of model structures using markup languages together with the ontology are reported. Using these methods three software utilities, including a graphical model editor, are implemented. Experimental results proved that these methods are effective for the modification of electrophysiological models.

cellPACK: a virtual mesoscope to model and visualize structural systems biology.

Science.gov (United States)

Johnson, Graham T; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

2015-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

Computing paths and cycles in biological interaction graphs

Directory of Open Access Journals (Sweden)

von Kamp Axel

2009-06-01

/negative paths and cycles in interaction graphs is an important method for network analysis in Systems Biology. This contribution draws the attention of the community to this important computational problem and provides a number of new algorithms, partially specifically tailored for biological interaction graphs. All algorithms have been implemented in the CellNetAnalyzer framework which can be downloaded for academic use at http://www.mpi-magdeburg.mpg.de/projects/cna/cna.html.

Systems Biology for Organotypic Cell Cultures

Energy Technology Data Exchange (ETDEWEB)

Grego, Sonia [RTI International, Research Triangle Park, NC (United States); Dougherty, Edward R. [Texas A & M Univ., College Station, TX (United States); Alexander, Francis J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Auerbach, Scott S. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Berridge, Brian R. [GlaxoSmithKline, Research Triangle Park, NC (United States); Bittner, Michael L. [Translational Genomics Research Inst., Phoenix, AZ (United States); Casey, Warren [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Cooley, Philip C. [RTI International, Research Triangle Park, NC (United States); Dash, Ajit [HemoShear Therapeutics, Charlottesville, VA (United States); Ferguson, Stephen S. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Fennell, Timothy R. [RTI International, Research Triangle Park, NC (United States); Hawkins, Brian T. [RTI International, Research Triangle Park, NC (United States); Hickey, Anthony J. [RTI International, Research Triangle Park, NC (United States); Kleensang, Andre [Johns Hopkins Univ., Baltimore, MD (United States). Center for Alternatives to Animal Testing; Liebman, Michael N. [IPQ Analytics, Kennett Square, PA (United States); Martin, Florian [Phillip Morris International, Neuchatel (Switzerland); Maull, Elizabeth A. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Paragas, Jason [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Qiao, Guilin [Defense Threat Reduction Agency, Ft. Belvoir, VA (United States); Ramaiahgari, Sreenivasa [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Sumner, Susan J. [RTI International, Research Triangle Park, NC (United States); Yoon, Miyoung [The Hamner Inst. for Health Sciences, Research Triangle Park, NC (United States); ScitoVation, Research Triangle Park, NC (United States)

2016-08-04

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data. This consensus report summarizes the discussions held.

Graphics processing units in bioinformatics, computational biology and systems biology.

Science.gov (United States)

Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

2017-09-01

Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

International Nuclear Information System (INIS)

2016-01-01

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

Energy Technology Data Exchange (ETDEWEB)

NONE

2016-06-15

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

Structure, function, and behaviour of computational models in systems biology.

Science.gov (United States)

Knüpfer, Christian; Beckstein, Clemens; Dittrich, Peter; Le Novère, Nicolas

2013-05-31

Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such "bio-models" necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. We present a conceptual framework - the meaning facets - which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model's components (structure), the meaning of the model's intended use (function), and the meaning of the model's dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research.

Modelling, abstraction, and computation in systems biology: A view from computer science.

Science.gov (United States)

Melham, Tom

2013-04-01

Systems biology is centrally engaged with computational modelling across multiple scales and at many levels of abstraction. Formal modelling, precise and formalised abstraction relationships, and computation also lie at the heart of computer science--and over the past decade a growing number of computer scientists have been bringing their discipline's core intellectual and computational tools to bear on biology in fascinating new ways. This paper explores some of the apparent points of contact between the two fields, in the context of a multi-disciplinary discussion on conceptual foundations of systems biology. Copyright © 2012 Elsevier Ltd. All rights reserved.

Computer Models and Automata Theory in Biology and Medicine

CERN Document Server

Baianu, I C

2004-01-01

The applications of computers to biological and biomedical problem solving goes back to the very beginnings of computer science, automata theory [1], and mathematical biology [2]. With the advent of more versatile and powerful computers, biological and biomedical applications of computers have proliferated so rapidly that it would be virtually impossible to compile a comprehensive review of all developments in this field. Limitations of computer simulations in biology have also come under close scrutiny, and claims have been made that biological systems have limited information processing power [3]. Such general conjectures do not, however, deter biologists and biomedical researchers from developing new computer applications in biology and medicine. Microprocessors are being widely employed in biological laboratories both for automatic data acquisition/processing and modeling; one particular area, which is of great biomedical interest, involves fast digital image processing and is already established for rout...

Computational Modeling of Biological Systems From Molecules to Pathways

CERN Document Server

2012-01-01

Computational modeling is emerging as a powerful new approach for studying and manipulating biological systems. Many diverse methods have been developed to model, visualize, and rationally alter these systems at various length scales, from atomic resolution to the level of cellular pathways. Processes taking place at larger time and length scales, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. Computational Modeling of Biological Systems: From Molecules to Pathways provides an overview of established computational methods for the modeling of biologically and medically relevant systems. It is suitable for researchers and professionals working in the fields of biophysics, computational biology, systems biology, and molecular medicine.

Final report for Conference Support Grant "From Computational Biophysics to Systems Biology - CBSB12"

Energy Technology Data Exchange (ETDEWEB)

Hansmann, Ulrich H.E.

2012-07-02

This report summarizes the outcome of the international workshop From Computational Biophysics to Systems Biology (CBSB12) which was held June 3-5, 2012, at the University of Tennessee Conference Center in Knoxville, TN, and supported by DOE through the Conference Support Grant 120174. The purpose of CBSB12 was to provide a forum for the interaction between a data-mining interested systems biology community and a simulation and first-principle oriented computational biophysics/biochemistry community. CBSB12 was the sixth in a series of workshops of the same name organized in recent years, and the second that has been held in the USA. As in previous years, it gave researchers from physics, biology, and computer science an opportunity to acquaint each other with current trends in computational biophysics and systems biology, to explore venues of cooperation, and to establish together a detailed understanding of cells at a molecular level. The conference grant of $10,000 was used to cover registration fees and provide travel fellowships to selected students and postdoctoral scientists. By educating graduate students and providing a forum for young scientists to perform research into the working of cells at a molecular level, the workshop adds to DOE's mission of paving the way to exploit the abilities of living systems to capture, store and utilize energy.

Developmental biology, the stem cell of biological disciplines

OpenAIRE

Gilbert, Scott F.

2017-01-01

Developmental biology (including embryology) is proposed as "the stem cell of biological disciplines.” Genetics, cell biology, oncology, immunology, evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental biology. Moreover, developmental biology continues to roll on, budding off more disciplines, while retaining its own identity. While its descendant disciplines differentiate into sciences with a restricted set of paradigms, examples, and techniques, ...

Ranked retrieval of Computational Biology models.

Science.gov (United States)

Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

2010-08-11

The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

Translational environmental biology: cell biology informing conservation.

Science.gov (United States)

Traylor-Knowles, Nikki; Palumbi, Stephen R

2014-05-01

Typically, findings from cell biology have been beneficial for preventing human disease. However, translational applications from cell biology can also be applied to conservation efforts, such as protecting coral reefs. Recent efforts to understand the cell biological mechanisms maintaining coral health such as innate immunity and acclimatization have prompted new developments in conservation. Similar to biomedicine, we urge that future efforts should focus on better frameworks for biomarker development to protect coral reefs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Developmental biology, the stem cell of biological disciplines.

Science.gov (United States)

Gilbert, Scott F

2017-12-01

Developmental biology (including embryology) is proposed as "the stem cell of biological disciplines." Genetics, cell biology, oncology, immunology, evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental biology. Moreover, developmental biology continues to roll on, budding off more disciplines, while retaining its own identity. While its descendant disciplines differentiate into sciences with a restricted set of paradigms, examples, and techniques, developmental biology remains vigorous, pluripotent, and relatively undifferentiated. In many disciplines, especially in evolutionary biology and oncology, the developmental perspective is being reasserted as an important research program.

Computer simulation in cell radiobiology

International Nuclear Information System (INIS)

Yakovlev, A.Y.; Zorin, A.V.

1988-01-01

This research monograph demonstrates the possible ways of using stochastic simulation for exploring cell kinetics, emphasizing the effects of cell radiobiology. In vitro kinetics of normal and irradiated cells is the main subject, but some approaches to the simulation of controlled cell systems are considered as well: the epithelium of the small intestine in mice taken as a case in point. Of particular interest is the evaluation of simulation modelling as a tool for gaining insight into biological processes and hence the new inferences from concrete experimental data, concerning regularities in cell population response to irradiation. The book is intended to stimulate interest among computer science specialists in developing new, more efficient means for the simulation of cell systems and to help radiobiologists in interpreting the experimental data

Fostering synergy between cell biology and systems biology.

Science.gov (United States)

Eddy, James A; Funk, Cory C; Price, Nathan D

2015-08-01

In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Computational biology and bioinformatics in Nigeria.

Science.gov (United States)

Fatumo, Segun A; Adoga, Moses P; Ojo, Opeolu O; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

2014-04-01

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.

Computational biology and bioinformatics in Nigeria.

Directory of Open Access Journals (Sweden)

Segun A Fatumo

2014-04-01

Full Text Available Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.

Application of computational intelligence to biology

CERN Document Server

Sekhar, Akula

2016-01-01

This book is a contribution of translational and allied research to the proceedings of the International Conference on Computational Intelligence and Soft Computing. It explains how various computational intelligence techniques can be applied to investigate various biological problems. It is a good read for Research Scholars, Engineers, Medical Doctors and Bioinformatics researchers.

The fusion of biology, computer science, and engineering: towards efficient and successful synthetic biology.

Science.gov (United States)

Linshiz, Gregory; Goldberg, Alex; Konry, Tania; Hillson, Nathan J

2012-01-01

Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.

Bioinformatics approaches to single-cell analysis in developmental biology.

Science.gov (United States)

Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H

2016-03-01

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European

Computational biology for ageing

Science.gov (United States)

Wieser, Daniela; Papatheodorou, Irene; Ziehm, Matthias; Thornton, Janet M.

2011-01-01

High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions. PMID:21115530

Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges.

Science.gov (United States)

Yin, Zekun; Lan, Haidong; Tan, Guangming; Lu, Mian; Vasilakos, Athanasios V; Liu, Weiguo

2017-01-01

The last decade has witnessed an explosion in the amount of available biological sequence data, due to the rapid progress of high-throughput sequencing projects. However, the biological data amount is becoming so great that traditional data analysis platforms and methods can no longer meet the need to rapidly perform data analysis tasks in life sciences. As a result, both biologists and computer scientists are facing the challenge of gaining a profound insight into the deepest biological functions from big biological data. This in turn requires massive computational resources. Therefore, high performance computing (HPC) platforms are highly needed as well as efficient and scalable algorithms that can take advantage of these platforms. In this paper, we survey the state-of-the-art HPC platforms for big biological data analytics. We first list the characteristics of big biological data and popular computing platforms. Then we provide a taxonomy of different biological data analysis applications and a survey of the way they have been mapped onto various computing platforms. After that, we present a case study to compare the efficiency of different computing platforms for handling the classical biological sequence alignment problem. At last we discuss the open issues in big biological data analytics.

Genome annotation in a community college cell biology lab.

Science.gov (United States)

Beagley, C Timothy

2013-01-01

The Biology Department at Salt Lake Community College has used the IMG-ACT toolbox to introduce a genome mapping and annotation exercise into the laboratory portion of its Cell Biology course. This project provides students with an authentic inquiry-based learning experience while introducing them to computational biology and contemporary learning skills. Additionally, the project strengthens student understanding of the scientific method and contributes to student learning gains in curricular objectives centered around basic molecular biology, specifically, the Central Dogma. Importantly, inclusion of this project in the laboratory course provides students with a positive learning environment and allows for the use of cooperative learning strategies to increase overall student success. Copyright © 2012 International Union of Biochemistry and Molecular Biology, Inc.

Computational structural biology: methods and applications

National Research Council Canada - National Science Library

Schwede, Torsten; Peitsch, Manuel Claude

2008-01-01

... sequencing reinforced the observation that structural information is needed to understand the detailed function and mechanism of biological molecules such as enzyme reactions and molecular recognition events. Furthermore, structures are obviously key to the design of molecules with new or improved functions. In this context, computational structural biology...

Discovery of novel bacterial toxins by genomics and computational biology.

Science.gov (United States)

Doxey, Andrew C; Mansfield, Michael J; Montecucco, Cesare

2018-06-01

Hundreds and hundreds of bacterial protein toxins are presently known. Traditionally, toxin identification begins with pathological studies of bacterial infectious disease. Following identification and cultivation of a bacterial pathogen, the protein toxin is purified from the culture medium and its pathogenic activity is studied using the methods of biochemistry and structural biology, cell biology, tissue and organ biology, and appropriate animal models, supplemented by bioimaging techniques. The ongoing and explosive development of high-throughput DNA sequencing and bioinformatic approaches have set in motion a revolution in many fields of biology, including microbiology. One consequence is that genes encoding novel bacterial toxins can be identified by bioinformatic and computational methods based on previous knowledge accumulated from studies of the biology and pathology of thousands of known bacterial protein toxins. Starting from the paradigmatic cases of diphtheria toxin, tetanus and botulinum neurotoxins, this review discusses traditional experimental approaches as well as bioinformatics and genomics-driven approaches that facilitate the discovery of novel bacterial toxins. We discuss recent work on the identification of novel botulinum-like toxins from genera such as Weissella, Chryseobacterium, and Enteroccocus, and the implications of these computationally identified toxins in the field. Finally, we discuss the promise of metagenomics in the discovery of novel toxins and their ecological niches, and present data suggesting the existence of uncharacterized, botulinum-like toxin genes in insect gut metagenomes. Copyright © 2018. Published by Elsevier Ltd.

Toward computational cumulative biology by combining models of biological datasets.

Science.gov (United States)

Faisal, Ali; Peltonen, Jaakko; Georgii, Elisabeth; Rung, Johan; Kaski, Samuel

2014-01-01

A main challenge of data-driven sciences is how to make maximal use of the progressively expanding databases of experimental datasets in order to keep research cumulative. We introduce the idea of a modeling-based dataset retrieval engine designed for relating a researcher's experimental dataset to earlier work in the field. The search is (i) data-driven to enable new findings, going beyond the state of the art of keyword searches in annotations, (ii) modeling-driven, to include both biological knowledge and insights learned from data, and (iii) scalable, as it is accomplished without building one unified grand model of all data. Assuming each dataset has been modeled beforehand, by the researchers or automatically by database managers, we apply a rapidly computable and optimizable combination model to decompose a new dataset into contributions from earlier relevant models. By using the data-driven decomposition, we identify a network of interrelated datasets from a large annotated human gene expression atlas. While tissue type and disease were major driving forces for determining relevant datasets, the found relationships were richer, and the model-based search was more accurate than the keyword search; moreover, it recovered biologically meaningful relationships that are not straightforwardly visible from annotations-for instance, between cells in different developmental stages such as thymocytes and T-cells. Data-driven links and citations matched to a large extent; the data-driven links even uncovered corrections to the publication data, as two of the most linked datasets were not highly cited and turned out to have wrong publication entries in the database.

Molecular biology of the cell

CERN Document Server

Alberts, Bruce; Lewis, Julian

2000-01-01

Molecular Biology of the Cell is the classic in-dept text reference in cell biology. By extracting the fundamental concepts from this enormous and ever-growing field, the authors tell the story of cell biology, and create a coherent framework through which non-expert readers may approach the subject. Written in clear and concise language, and beautifully illustrated, the book is enjoyable to read, and it provides a clear sense of the excitement of modern biology. Molecular Biology of the Cell sets forth the current understanding of cell biology (completely updated as of Autumn 2001), and it explores the intriguing implications and possibilities of the great deal that remains unknown. The hallmark features of previous editions continue in the Fourth Edition. The book is designed with a clean and open, single-column layout. The art program maintains a completely consistent format and style, and includes over 1,600 photographs, electron micrographs, and original drawings by the authors. Clear and concise concept...

Biological fuel cells and their applications

OpenAIRE

Shukla, AK; Suresh, P; Berchmans, S; Rajendran, A

2004-01-01

One type of genuine fuel cell that does hold promise in the long-term is the biological fuel cell. Unlike conventional fuel cells, which employ hydrogen, ethanol and methanol as fuel, biological fuel cells use organic products produced by metabolic processes or use organic electron donors utilized in the growth processes as fuels for current generation. A distinctive feature of biological fuel cells is that the electrode reactions are controlled by biocatalysts, i.e. the biological redox-reac...

Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

Energy Technology Data Exchange (ETDEWEB)

Guerrier, C. [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Holcman, D., E-mail: david.holcman@ens.fr [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Mathematical Institute, Oxford OX2 6GG, Newton Institute (United Kingdom)

2017-07-01

The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.

Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

International Nuclear Information System (INIS)

Guerrier, C.; Holcman, D.

2017-01-01

The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.

Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

CERN Document Server

2017-01-01

This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

Micro-Computers in Biology Inquiry.

Science.gov (United States)

Barnato, Carolyn; Barrett, Kathy

1981-01-01

Describes the modification of computer programs (BISON and POLLUT) to accommodate species and areas indigenous to the Pacific Coast area. Suggests that these programs, suitable for PET microcomputers, may foster a long-term, ongoing, inquiry-directed approach in biology. (DS)

Multiway modeling and analysis in stem cell systems biology

Directory of Open Access Journals (Sweden)

Vandenberg Scott L

2008-07-01

Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

6th International Conference on Practical Applications of Computational Biology & Bioinformatics

CERN Document Server

Luscombe, Nicholas; Fdez-Riverola, Florentino; Rodríguez, Juan; Practical Applications of Computational Biology & Bioinformatics

2012-01-01

The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable.. The analysis of the datasets of Next Generation Sequencing needs new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Also Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. This book presents the results of the  6th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, 28-30th March, 2012 which brought together interdisciplinary scientists that have a strong background in the biological and computational sciences.

Systems Biology and Stem Cell Pluripotency

DEFF Research Database (Denmark)

Mashayekhi, Kaveh; Hall, Vanessa Jane; Freude, Kristine

2016-01-01

Recent breakthroughs in stem cell biology have accelerated research in the area of regenerative medicine. Over the past years, it has become possible to derive patient-specific stem cells which can be used to generate different cell populations for potential cell therapy. Systems biological...... modeling of stem cell pluripotency and differentiation have largely been based on prior knowledge of signaling pathways, gene regulatory networks, and epigenetic factors. However, there is a great need to extend the complexity of the modeling and to integrate different types of data, which would further...... improve systems biology and its uses in the field. In this chapter, we first give a general background on stem cell biology and regenerative medicine. Stem cell potency is introduced together with the hierarchy of stem cells ranging from pluripotent embryonic stem cells (ESCs) and induced pluripotent stem...

Studying cell biology in the skin.

Science.gov (United States)

Morrow, Angel; Lechler, Terry

2015-11-15

Advances in cell biology have often been driven by studies in diverse organisms and cell types. Although there are technical reasons for why different cell types are used, there are also important physiological reasons. For example, ultrastructural studies of vesicle transport were aided by the use of professional secretory cell types. The use of tissues/primary cells has the advantage not only of using cells that are adapted to the use of certain cell biological machinery, but also of highlighting the physiological roles of this machinery. Here we discuss advantages of the skin as a model system. We discuss both advances in cell biology that used the skin as a driving force and future prospects for use of the skin to understand basic cell biology. A unique combination of characteristics and tools makes the skin a useful in vivo model system for many cell biologists. © 2015 Morrow and Lechler. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

How Computers are Arming biology!

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 23; Issue 1. In-vitro to In-silico - How Computers are Arming biology! Geetha Sugumaran Sushila Rajagopal. Face to Face Volume 23 Issue 1 January 2018 pp 83-102. Fulltext. Click here to view fulltext PDF. Permanent link:

Computational Biology Support: RECOMB Conference Series (Conference Support)

Energy Technology Data Exchange (ETDEWEB)

Michael Waterman

2006-06-15

This funding was support for student and postdoctoral attendance at the Annual Recomb Conference from 2001 to 2005. The RECOMB Conference series was founded in 1997 to provide a scientific forum for theoretical advances in computational biology and their applications in molecular biology and medicine. The conference series aims at attracting research contributions in all areas of computational molecular biology. Typical, but not exclusive, the topics of interest are: Genomics, Molecular sequence analysis, Recognition of genes and regulatory elements, Molecular evolution, Protein structure, Structural genomics, Gene Expression, Gene Networks, Drug Design, Combinatorial libraries, Computational proteomics, and Structural and functional genomics. The origins of the conference came from the mathematical and computational side of the field, and there remains to be a certain focus on computational advances. However, the effective use of computational techniques to biological innovation is also an important aspect of the conference. The conference had a growing number of attendees, topping 300 in recent years and often exceeding 500. The conference program includes between 30 and 40 contributed papers, that are selected by a international program committee with around 30 experts during a rigorous review process rivaling the editorial procedure for top-rate scientific journals. In previous years papers selection has been made from up to 130--200 submissions from well over a dozen countries. 10-page extended abstracts of the contributed papers are collected in a volume published by ACM Press and Springer, and are available at the conference. Full versions of a selection of the papers are published annually in a special issue of the Journal of Computational Biology devoted to the RECOMB Conference. A further point in the program is a lively poster session. From 120-300 posters have been presented each year at RECOMB 2000. One of the highlights of each RECOMB conference is a

Mammalian cell biology

International Nuclear Information System (INIS)

Elkind, M.M.

1979-01-01

This section contains summaries of research on mechanisms of lethality and radioinduced changes in mammalian cell properties, new cell systems for the study of the biology of mutation and neoplastic transformation, and comparative properties of ionizing radiations

Evolutionary cell biology: two origins, one objective.

Science.gov (United States)

Lynch, Michael; Field, Mark C; Goodson, Holly V; Malik, Harmit S; Pereira-Leal, José B; Roos, David S; Turkewitz, Aaron P; Sazer, Shelley

2014-12-02

All aspects of biological diversification ultimately trace to evolutionary modifications at the cellular level. This central role of cells frames the basic questions as to how cells work and how cells come to be the way they are. Although these two lines of inquiry lie respectively within the traditional provenance of cell biology and evolutionary biology, a comprehensive synthesis of evolutionary and cell-biological thinking is lacking. We define evolutionary cell biology as the fusion of these two eponymous fields with the theoretical and quantitative branches of biochemistry, biophysics, and population genetics. The key goals are to develop a mechanistic understanding of general evolutionary processes, while specifically infusing cell biology with an evolutionary perspective. The full development of this interdisciplinary field has the potential to solve numerous problems in diverse areas of biology, including the degree to which selection, effectively neutral processes, historical contingencies, and/or constraints at the chemical and biophysical levels dictate patterns of variation for intracellular features. These problems can now be examined at both the within- and among-species levels, with single-cell methodologies even allowing quantification of variation within genotypes. Some results from this emerging field have already had a substantial impact on cell biology, and future findings will significantly influence applications in agriculture, medicine, environmental science, and synthetic biology.

The thermodynamic efficiency of computations made in cells across the range of life

Science.gov (United States)

Kempes, Christopher P.; Wolpert, David; Cohen, Zachary; Pérez-Mercader, Juan

2017-11-01

Biological organisms must perform computation as they grow, reproduce and evolve. Moreover, ever since Landauer's bound was proposed, it has been known that all computation has some thermodynamic cost-and that the same computation can be achieved with greater or smaller thermodynamic cost depending on how it is implemented. Accordingly an important issue concerning the evolution of life is assessing the thermodynamic efficiency of the computations performed by organisms. This issue is interesting both from the perspective of how close life has come to maximally efficient computation (presumably under the pressure of natural selection), and from the practical perspective of what efficiencies we might hope that engineered biological computers might achieve, especially in comparison with current computational systems. Here we show that the computational efficiency of translation, defined as free energy expended per amino acid operation, outperforms the best supercomputers by several orders of magnitude, and is only about an order of magnitude worse than the Landauer bound. However, this efficiency depends strongly on the size and architecture of the cell in question. In particular, we show that the useful efficiency of an amino acid operation, defined as the bulk energy per amino acid polymerization, decreases for increasing bacterial size and converges to the polymerization cost of the ribosome. This cost of the largest bacteria does not change in cells as we progress through the major evolutionary shifts to both single- and multicellular eukaryotes. However, the rates of total computation per unit mass are non-monotonic in bacteria with increasing cell size, and also change across different biological architectures, including the shift from unicellular to multicellular eukaryotes. This article is part of the themed issue 'Reconceptualizing the origins of life'.

9th International Conference on Practical Applications of Computational Biology and Bioinformatics

CERN Document Server

Rocha, Miguel; Fdez-Riverola, Florentino; Paz, Juan

2015-01-01

This proceedings presents recent practical applications of Computational Biology and  Bioinformatics. It contains the proceedings of the 9th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, at June 3rd-5th, 2015. The International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) is an annual international meeting dedicated to emerging and challenging applied research in Bioinformatics and Computational Biology. Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis o...

Extending and Applying Spartan to Perform Temporal Sensitivity Analyses for Predicting Changes in Influential Biological Pathways in Computational Models.

Science.gov (United States)

Alden, Kieran; Timmis, Jon; Andrews, Paul S; Veiga-Fernandes, Henrique; Coles, Mark

2017-01-01

Through integrating real time imaging, computational modelling, and statistical analysis approaches, previous work has suggested that the induction of and response to cell adhesion factors is the key initiating pathway in early lymphoid tissue development, in contrast to the previously accepted view that the process is triggered by chemokine mediated cell recruitment. These model derived hypotheses were developed using spartan, an open-source sensitivity analysis toolkit designed to establish and understand the relationship between a computational model and the biological system that model captures. Here, we extend the functionality available in spartan to permit the production of statistical analyses that contrast the behavior exhibited by a computational model at various simulated time-points, enabling a temporal analysis that could suggest whether the influence of biological mechanisms changes over time. We exemplify this extended functionality by using the computational model of lymphoid tissue development as a time-lapse tool. By generating results at twelve- hour intervals, we show how the extensions to spartan have been used to suggest that lymphoid tissue development could be biphasic, and predict the time-point when a switch in the influence of biological mechanisms might occur.

Computational biology in the cloud: methods and new insights from computing at scale.

Science.gov (United States)

Kasson, Peter M

2013-01-01

The past few years have seen both explosions in the size of biological data sets and the proliferation of new, highly flexible on-demand computing capabilities. The sheer amount of information available from genomic and metagenomic sequencing, high-throughput proteomics, experimental and simulation datasets on molecular structure and dynamics affords an opportunity for greatly expanded insight, but it creates new challenges of scale for computation, storage, and interpretation of petascale data. Cloud computing resources have the potential to help solve these problems by offering a utility model of computing and storage: near-unlimited capacity, the ability to burst usage, and cheap and flexible payment models. Effective use of cloud computing on large biological datasets requires dealing with non-trivial problems of scale and robustness, since performance-limiting factors can change substantially when a dataset grows by a factor of 10,000 or more. New computing paradigms are thus often needed. The use of cloud platforms also creates new opportunities to share data, reduce duplication, and to provide easy reproducibility by making the datasets and computational methods easily available.

Feedback dynamics and cell function: Why systems biology is called Systems Biology.

Science.gov (United States)

Wolkenhauer, Olaf; Mesarovic, Mihajlo

2005-05-01

A new paradigm, like Systems Biology, should challenge the way research has been conducted previously. This Opinion article aims to present Systems Biology, not as the application of engineering principles to biology but as a merger of systems- and control theory with molecular- and cell biology. In our view, the central dogma of Systems Biology is that it is system dynamics that gives rise to the functioning and function of cells. The concepts of feedback regulation and control of pathways and the coordination of cell function are emphasized as an important area of Systems Biology research. The hurdles and risks for this area are discussed from the perspective of dynamic pathway modelling. Most of all, the aim of this article is to promote mathematical modelling and simulation as a part of molecular- and cell biology. Systems Biology is a success if it is widely accepted that there is nothing more practical than a good theory.

Computational Biomechanics Theoretical Background and BiologicalBiomedical Problems

CERN Document Server

Tanaka, Masao; Nakamura, Masanori

2012-01-01

Rapid developments have taken place in biological/biomedical measurement and imaging technologies as well as in computer analysis and information technologies. The increase in data obtained with such technologies invites the reader into a virtual world that represents realistic biological tissue or organ structures in digital form and allows for simulation and what is called “in silico medicine.” This volume is the third in a textbook series and covers both the basics of continuum mechanics of biosolids and biofluids and the theoretical core of computational methods for continuum mechanics analyses. Several biomechanics problems are provided for better understanding of computational modeling and analysis. Topics include the mechanics of solid and fluid bodies, fundamental characteristics of biosolids and biofluids, computational methods in biomechanics analysis/simulation, practical problems in orthopedic biomechanics, dental biomechanics, ophthalmic biomechanics, cardiovascular biomechanics, hemodynamics...

DOE EPSCoR Initiative in Structural and computational Biology/Bioinformatics

Energy Technology Data Exchange (ETDEWEB)

Wallace, Susan S.

2008-02-21

The overall goal of the DOE EPSCoR Initiative in Structural and Computational Biology was to enhance the competiveness of Vermont research in these scientific areas. To develop self-sustaining infrastructure, we increased the critical mass of faculty, developed shared resources that made junior researchers more competitive for federal research grants, implemented programs to train graduate and undergraduate students who participated in these research areas and provided seed money for research projects. During the time period funded by this DOE initiative: (1) four new faculty were recruited to the University of Vermont using DOE resources, three in Computational Biology and one in Structural Biology; (2) technical support was provided for the Computational and Structural Biology facilities; (3) twenty-two graduate students were directly funded by fellowships; (4) fifteen undergraduate students were supported during the summer; and (5) twenty-eight pilot projects were supported. Taken together these dollars resulted in a plethora of published papers, many in high profile journals in the fields and directly impacted competitive extramural funding based on structural or computational biology resulting in 49 million dollars awarded in grants (Appendix I), a 600% return on investment by DOE, the State and University.

7th International Conference on Practical Applications of Computational Biology & Bioinformatics

CERN Document Server

Nanni, Loris; Rocha, Miguel; Fdez-Riverola, Florentino

2013-01-01

The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Within this scenario of increasing data availability, Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we ...

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

Science.gov (United States)

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

2010-02-01

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell

Learning Cell Biology as a Team: A Project-Based Approach to Upper-Division Cell Biology

Science.gov (United States)

Wright, Robin; Boggs, James

2002-01-01

To help students develop successful strategies for learning how to learn and communicate complex information in cell biology, we developed a quarter-long cell biology class based on team projects. Each team researches a particular human disease and presents information about the cellular structure or process affected by the disease, the cellular…

Teaching Cell Biology in Primary Schools

Directory of Open Access Journals (Sweden)

Francele de Abreu Carlan

2014-01-01

Full Text Available Basic concepts of cell biology are essential for scientific literacy. However, because many aspects of cell theory and cell functioning are quite abstract, students experience difficulties understanding them. In this study, we investigated whether diverse teaching resources such as the use of replicas of Leeuwenhoek’s microscope, visualization of cells using an optical microscope, construction of three-dimensional cell models, and reading of a comic book about cells could mitigate the difficulties encountered when teaching cell biology to 8th-grade primary school students. The results suggest that these didactic activities improve students’ ability to learn concrete concepts about cell biology, such as the composition of living beings, growth, and cicatrization. Also, the development of skills was observed, as, for example, the notion of cell size. However, no significant improvements were observed in students’ ability to learn about abstract topics, such as the structures of subcellular organelles and their functions. These results suggest that many students in this age have not yet concluded Piaget’s concrete operational stage, indicating that the concepts required for the significant learning of abstract subjects need to be explored more thoroughly in the process of designing programs that introduce primary school students to cell biology.

Defining Biological Networks for Noise Buffering and Signaling Sensitivity Using Approximate Bayesian Computation

Directory of Open Access Journals (Sweden)

Shuqiang Wang

2014-01-01

Full Text Available Reliable information processing in cells requires high sensitivity to changes in the input signal but low sensitivity to random fluctuations in the transmitted signal. There are often many alternative biological circuits qualifying for this biological function. Distinguishing theses biological models and finding the most suitable one are essential, as such model ranking, by experimental evidence, will help to judge the support of the working hypotheses forming each model. Here, we employ the approximate Bayesian computation (ABC method based on sequential Monte Carlo (SMC to search for biological circuits that can maintain signaling sensitivity while minimizing noise propagation, focusing on cases where the noise is characterized by rapid fluctuations. By systematically analyzing three-component circuits, we rank these biological circuits and identify three-basic-biological-motif buffering noise while maintaining sensitivity to long-term changes in input signals. We discuss in detail a particular implementation in control of nutrient homeostasis in yeast. The principal component analysis of the posterior provides insight into the nature of the reaction between nodes.

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

Science.gov (United States)

Pârvu, Ovidiu; Gilbert, David

2016-01-01

, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

Biological 2-Input Decoder Circuit in Human Cells

Science.gov (United States)

2015-01-01

Decoders are combinational circuits that convert information from n inputs to a maximum of 2n outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions. PMID:24694115

Biological 2-input decoder circuit in human cells.

Science.gov (United States)

Guinn, Michael; Bleris, Leonidas

2014-08-15

Decoders are combinational circuits that convert information from n inputs to a maximum of 2(n) outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions.

The Cell Collective: Toward an open and collaborative approach to systems biology

Directory of Open Access Journals (Sweden)

Helikar Tomáš

2012-08-01

Full Text Available Abstract Background Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. Results The Cell Collective is a platform that allows the world-wide scientific community to create these models collectively. Its interface enables users to build and use models without specifying any mathematical equations or computer code - addressing one of the major hurdles with computational research. In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time. Conclusions The Cell Collective is a web-based platform that enables laboratory scientists from across the globe to collaboratively build large-scale models of various biological processes, and simulate/analyze them in real time. In this manuscript, we show examples of its application to a large-scale model of signal transduction.

Integrating cell biology and proteomic approaches in plants.

Science.gov (United States)

Takáč, Tomáš; Šamajová, Olga; Šamaj, Jozef

2017-10-03

Significant improvements of protein extraction, separation, mass spectrometry and bioinformatics nurtured advancements of proteomics during the past years. The usefulness of proteomics in the investigation of biological problems can be enhanced by integration with other experimental methods from cell biology, genetics, biochemistry, pharmacology, molecular biology and other omics approaches including transcriptomics and metabolomics. This review aims to summarize current trends integrating cell biology and proteomics in plant science. Cell biology approaches are most frequently used in proteomic studies investigating subcellular and developmental proteomes, however, they were also employed in proteomic studies exploring abiotic and biotic stress responses, vesicular transport, cytoskeleton and protein posttranslational modifications. They are used either for detailed cellular or ultrastructural characterization of the object subjected to proteomic study, validation of proteomic results or to expand proteomic data. In this respect, a broad spectrum of methods is employed to support proteomic studies including ultrastructural electron microscopy studies, histochemical staining, immunochemical localization, in vivo imaging of fluorescently tagged proteins and visualization of protein-protein interactions. Thus, cell biological observations on fixed or living cell compartments, cells, tissues and organs are feasible, and in some cases fundamental for the validation and complementation of proteomic data. Validation of proteomic data by independent experimental methods requires development of new complementary approaches. Benefits of cell biology methods and techniques are not sufficiently highlighted in current proteomic studies. This encouraged us to review most popular cell biology methods used in proteomic studies and to evaluate their relevance and potential for proteomic data validation and enrichment of purely proteomic analyses. We also provide examples of

11th International Conference on Practical Applications of Computational Biology & Bioinformatics

CERN Document Server

Mohamad, Mohd; Rocha, Miguel; Paz, Juan; Pinto, Tiago

2017-01-01

Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of r...

8th International Conference on Practical Applications of Computational Biology & Bioinformatics

CERN Document Server

Rocha, Miguel; Fdez-Riverola, Florentino; Santana, Juan

2014-01-01

Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...

10th International Conference on Practical Applications of Computational Biology & Bioinformatics

CERN Document Server

Rocha, Miguel; Fdez-Riverola, Florentino; Mayo, Francisco; Paz, Juan

2016-01-01

Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...

The emerging age of cell-free synthetic biology.

Science.gov (United States)

Smith, Mark Thomas; Wilding, Kristen M; Hunt, Jeremy M; Bennett, Anthony M; Bundy, Bradley C

2014-08-25

The engineering of and mastery over biological parts has catalyzed the emergence of synthetic biology. This field has grown exponentially in the past decade. As increasingly more applications of synthetic biology are pursued, more challenges are encountered, such as delivering genetic material into cells and optimizing genetic circuits in vivo. An in vitro or cell-free approach to synthetic biology simplifies and avoids many of the pitfalls of in vivo synthetic biology. In this review, we describe some of the innate features that make cell-free systems compelling platforms for synthetic biology and discuss emerging improvements of cell-free technologies. We also select and highlight recent and emerging applications of cell-free synthetic biology. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Analysis of undergraduate cell biology contents in Brazilian public universities.

Science.gov (United States)

Mermelstein, Claudia; Costa, Manoel Luis

2017-04-01

The enormous amount of information available in cell biology has created a challenge in selecting the core concepts we should be teaching our undergraduates. One way to define a set of essential core ideas in cell biology is to analyze what a specific cell biology community is teaching their students. Our main objective was to analyze the cell biology content currently being taught in Brazilian universities. We collected the syllabi of cell biology courses from public universities in Brazil and analyzed the frequency of cell biology topics in each course. We also compared the Brazilian data with the contents of a major cell biology textbook. Our analysis showed that while some cell biology topics such as plasma membrane and cytoskeleton was present in ∼100% of the Brazilian curricula analyzed others such as cell signaling and cell differentiation were present in only ∼35%. The average cell biology content taught in the Brazilian universities is quite different from what is presented in the textbook. We discuss several possible explanations for these observations. We also suggest a list with essential cell biology topics for any biological or biomedical undergraduate course. The comparative discussion of cell biology topics presented here could be valuable in other educational contexts. © 2017 The Authors. Cell Biology International Published by John Wiley & Sons Ltd on behalf of International Federation of Cell Biology.

Notions of similarity for computational biology models

KAUST Repository

Waltemath, Dagmar

2016-03-21

Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users\\' intuition about model similarity, and to support complex model searches in databases.

Notions of similarity for computational biology models

KAUST Repository

Waltemath, Dagmar; Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knuepfer, Christian; Liebermeister, Wolfram

2016-01-01

Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users' intuition about model similarity, and to support complex model searches in databases.

Proceedings of the first international conference on trends in cell and molecular biology: conference abstract book

International Nuclear Information System (INIS)

2015-01-01

This conference throws light on topics for understanding the importance of nanotechnology as a potential treatment option for some important diseases. Computational biology with its vibrant research outputs needs to be integrated with modern cell biology as a whole to understand, analyze and predict the impacts in a much better way. Papers relevant to INIS are indexed separately

2nd Colombian Congress on Computational Biology and Bioinformatics

CERN Document Server

Cristancho, Marco; Isaza, Gustavo; Pinzón, Andrés; Rodríguez, Juan

2014-01-01

This volume compiles accepted contributions for the 2nd Edition of the Colombian Computational Biology and Bioinformatics Congress CCBCOL, after a rigorous review process in which 54 papers were accepted for publication from 119 submitted contributions. Bioinformatics and Computational Biology are areas of knowledge that have emerged due to advances that have taken place in the Biological Sciences and its integration with Information Sciences. The expansion of projects involving the study of genomes has led the way in the production of vast amounts of sequence data which needs to be organized, analyzed and stored to understand phenomena associated with living organisms related to their evolution, behavior in different ecosystems, and the development of applications that can be derived from this analysis.  .

The ISCB Student Council Internship Program: Expanding computational biology capacity worldwide.

Science.gov (United States)

Anupama, Jigisha; Francescatto, Margherita; Rahman, Farzana; Fatima, Nazeefa; DeBlasio, Dan; Shanmugam, Avinash Kumar; Satagopam, Venkata; Santos, Alberto; Kolekar, Pandurang; Michaut, Magali; Guney, Emre

2018-01-01

Education and training are two essential ingredients for a successful career. On one hand, universities provide students a curriculum for specializing in one's field of study, and on the other, internships complement coursework and provide invaluable training experience for a fruitful career. Consequently, undergraduates and graduates are encouraged to undertake an internship during the course of their degree. The opportunity to explore one's research interests in the early stages of their education is important for students because it improves their skill set and gives their career a boost. In the long term, this helps to close the gap between skills and employability among students across the globe and balance the research capacity in the field of computational biology. However, training opportunities are often scarce for computational biology students, particularly for those who reside in less-privileged regions. Aimed at helping students develop research and academic skills in computational biology and alleviating the divide across countries, the Student Council of the International Society for Computational Biology introduced its Internship Program in 2009. The Internship Program is committed to providing access to computational biology training, especially for students from developing regions, and improving competencies in the field. Here, we present how the Internship Program works and the impact of the internship opportunities so far, along with the challenges associated with this program.

The ISCB Student Council Internship Program: Expanding computational biology capacity worldwide.

Directory of Open Access Journals (Sweden)

Jigisha Anupama

2018-01-01

Full Text Available Education and training are two essential ingredients for a successful career. On one hand, universities provide students a curriculum for specializing in one's field of study, and on the other, internships complement coursework and provide invaluable training experience for a fruitful career. Consequently, undergraduates and graduates are encouraged to undertake an internship during the course of their degree. The opportunity to explore one's research interests in the early stages of their education is important for students because it improves their skill set and gives their career a boost. In the long term, this helps to close the gap between skills and employability among students across the globe and balance the research capacity in the field of computational biology. However, training opportunities are often scarce for computational biology students, particularly for those who reside in less-privileged regions. Aimed at helping students develop research and academic skills in computational biology and alleviating the divide across countries, the Student Council of the International Society for Computational Biology introduced its Internship Program in 2009. The Internship Program is committed to providing access to computational biology training, especially for students from developing regions, and improving competencies in the field. Here, we present how the Internship Program works and the impact of the internship opportunities so far, along with the challenges associated with this program.

Physical Principles of Development of the State Standard of Biological Cell Polarizability

Science.gov (United States)

Shuvalov, G. V.; Generalov, K. V.; Generalov, V. M.; Kruchinina, M. V.; Koptev, E. S.; Minin, O. V.; Minin, I. V.

2018-03-01

A new state standard of biological cell polarizability based on micron-size latex particles has been developed. As a standard material, it is suggested to use polystyrene. Values of the polarizability calculated for erythrocytes and values of the polarizability of micron-size spherical latex particles measured with measuring-computing complexes agree within the limits of satisfactory relative error. The Standard allows one the unit of polarizability measurements [m3] to be assigned to cells and erythrocytes for the needs of medicine.

Novel opportunities for computational biology and sociology in drug discovery☆

Science.gov (United States)

Yao, Lixia; Evans, James A.; Rzhetsky, Andrey

2013-01-01

Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy–industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies. PMID:20349528

Novel opportunities for computational biology and sociology in drug discovery

Science.gov (United States)

Yao, Lixia

2009-01-01

Drug discovery today is impossible without sophisticated modeling and computation. In this review we touch on previous advances in computational biology and by tracing the steps involved in pharmaceutical development, we explore a range of novel, high value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry ties for scientific and human benefit. Attention to these opportunities could promise punctuated advance, and will complement the well-established computational work on which drug discovery currently relies. PMID:19674801

Revision history aware repositories of computational models of biological systems.

Science.gov (United States)

Miller, Andrew K; Yu, Tommy; Britten, Randall; Cooling, Mike T; Lawson, James; Cowan, Dougal; Garny, Alan; Halstead, Matt D B; Hunter, Peter J; Nickerson, David P; Nunns, Geo; Wimalaratne, Sarala M; Nielsen, Poul M F

2011-01-14

Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs) for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. We have extended the Physiome Model Repository software to be fully revision history aware

Revision history aware repositories of computational models of biological systems

Directory of Open Access Journals (Sweden)

Nickerson David P

2011-01-01

Full Text Available Abstract Background Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. Results We have extended the Physiome Model

Computational brain models: Advances from system biology and future challenges

Directory of Open Access Journals (Sweden)

George E. Barreto

2015-02-01

Full Text Available Computational brain models focused on the interactions between neurons and astrocytes, modeled via metabolic reconstructions, are reviewed. The large source of experimental data provided by the -omics techniques and the advance/application of computational and data-management tools are being fundamental. For instance, in the understanding of the crosstalk between these cells, the key neuroprotective mechanisms mediated by astrocytes in specific metabolic scenarios (1 and the identification of biomarkers for neurodegenerative diseases (2,3. However, the modeling of these interactions demands a clear view of the metabolic and signaling pathways implicated, but most of them are controversial and are still under evaluation (4. Hence, to gain insight into the complexity of these interactions a current view of the main pathways implicated in the neuron-astrocyte communication processes have been made from recent experimental reports and reviews. Furthermore, target problems, limitations and main conclusions have been identified from metabolic models of the brain reported from 2010. Finally, key aspects to take into account into the development of a computational model of the brain and topics that could be approached from a systems biology perspective in future research are highlighted.

Plant Systems Biology at the Single-Cell Level.

Science.gov (United States)

Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John

2017-11-01

Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.

A comprehensive approach to decipher biological computation to achieve next generation high-performance exascale computing.

Energy Technology Data Exchange (ETDEWEB)

James, Conrad D.; Schiess, Adrian B.; Howell, Jamie; Baca, Michael J.; Partridge, L. Donald; Finnegan, Patrick Sean; Wolfley, Steven L.; Dagel, Daryl James; Spahn, Olga Blum; Harper, Jason C.; Pohl, Kenneth Roy; Mickel, Patrick R.; Lohn, Andrew; Marinella, Matthew

2013-10-01

The human brain (volume=1200cm3) consumes 20W and is capable of performing > 10^16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m^3 and 3MW, giving the brain a 10^12 advantage in operations/s/W/cm^3. Thus, to reach exascale computation, two achievements are required: 1) improved understanding of computation in biological tissue, and 2) a paradigm shift towards neuromorphic computing where hardware circuits mimic properties of neural tissue. To address 1), we will interrogate corticostriatal networks in mouse brain tissue slices, specifically with regard to their frequency filtering capabilities as a function of input stimulus. To address 2), we will instantiate biological computing characteristics such as multi-bit storage into hardware devices with future computational and memory applications. Resistive memory devices will be modeled, designed, and fabricated in the MESA facility in consultation with our internal and external collaborators.

Converting differential-equation models of biological systems to membrane computing.

Science.gov (United States)

Muniyandi, Ravie Chandren; Zin, Abdullah Mohd; Sanders, J W

2013-12-01

This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Dancing Styles of Collective Cell Migration: Image-Based Computational Analysis of JRAB/MICAL-L2.

Science.gov (United States)

Sakane, Ayuko; Yoshizawa, Shin; Yokota, Hideo; Sasaki, Takuya

2018-01-01

Collective cell migration is observed during morphogenesis, angiogenesis, and wound healing, and this type of cell migration also contributes to efficient metastasis in some kinds of cancers. Because collectively migrating cells are much better organized than a random assemblage of individual cells, there seems to be a kind of order in migrating clusters. Extensive research has identified a large number of molecules involved in collective cell migration, and these factors have been analyzed using dramatic advances in imaging technology. To date, however, it remains unclear how myriad cells are integrated as a single unit. Recently, we observed unbalanced collective cell migrations that can be likened to either precision dancing or awa-odori , Japanese traditional dancing similar to the style at Rio Carnival, caused by the impairment of the conformational change of JRAB/MICAL-L2. This review begins with a brief history of image-based computational analyses on cell migration, explains why quantitative analysis of the stylization of collective cell behavior is difficult, and finally introduces our recent work on JRAB/MICAL-L2 as a successful example of the multidisciplinary approach combining cell biology, live imaging, and computational biology. In combination, these methods have enabled quantitative evaluations of the "dancing style" of collective cell migration.

Fundamentals of bioinformatics and computational biology methods and exercises in matlab

CERN Document Server

Singh, Gautam B

2015-01-01

This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolbox™. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research. The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence compar...

Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

OpenAIRE

Shuo Gu; Jianfeng Pei

2017-01-01

With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regula...

Parallel metaheuristics in computational biology: an asynchronous cooperative enhanced scatter search method

OpenAIRE

Penas, David R.; González, Patricia; Egea, José A.; Banga, Julio R.; Doallo, Ramón

2015-01-01

Metaheuristics are gaining increased attention as efficient solvers for hard global optimization problems arising in bioinformatics and computational systems biology. Scatter Search (SS) is one of the recent outstanding algorithms in that class. However, its application to very hard problems, like those considering parameter estimation in dynamic models of systems biology, still results in excessive computation times. In order to reduce the computational cost of the SS and improve its success...

Artificial cell mimics as simplified models for the study of cell biology.

Science.gov (United States)

Salehi-Reyhani, Ali; Ces, Oscar; Elani, Yuval

2017-07-01

Living cells are hugely complex chemical systems composed of a milieu of distinct chemical species (including DNA, proteins, lipids, and metabolites) interconnected with one another through a vast web of interactions: this complexity renders the study of cell biology in a quantitative and systematic manner a difficult task. There has been an increasing drive towards the utilization of artificial cells as cell mimics to alleviate this, a development that has been aided by recent advances in artificial cell construction. Cell mimics are simplified cell-like structures, composed from the bottom-up with precisely defined and tunable compositions. They allow specific facets of cell biology to be studied in isolation, in a simplified environment where control of variables can be achieved without interference from a living and responsive cell. This mini-review outlines the core principles of this approach and surveys recent key investigations that use cell mimics to address a wide range of biological questions. It will also place the field in the context of emerging trends, discuss the associated limitations, and outline future directions of the field. Impact statement Recent years have seen an increasing drive to construct cell mimics and use them as simplified experimental models to replicate and understand biological phenomena in a well-defined and controlled system. By summarizing the advances in this burgeoning field, and using case studies as a basis for discussion on the limitations and future directions of this approach, it is hoped that this minireview will spur others in the experimental biology community to use artificial cells as simplified models with which to probe biological systems.

Introducing Mammalian Cell Culture and Cell Viability Techniques in the Undergraduate Biology Laboratory.

Science.gov (United States)

Bowey-Dellinger, Kristen; Dixon, Luke; Ackerman, Kristin; Vigueira, Cynthia; Suh, Yewseok K; Lyda, Todd; Sapp, Kelli; Grider, Michael; Crater, Dinene; Russell, Travis; Elias, Michael; Coffield, V McNeil; Segarra, Verónica A

2017-01-01

Undergraduate students learn about mammalian cell culture applications in introductory biology courses. However, laboratory modules are rarely designed to provide hands-on experience with mammalian cells or teach cell culture techniques, such as trypsinization and cell counting. Students are more likely to learn about cell culture using bacteria or yeast, as they are typically easier to grow, culture, and manipulate given the equipment, tools, and environment of most undergraduate biology laboratories. In contrast, the utilization of mammalian cells requires a dedicated biological safety cabinet and rigorous antiseptic techniques. For this reason, we have devised a laboratory module and method herein that familiarizes students with common cell culture procedures, without the use of a sterile hood or large cell culture facility. Students design and perform a time-efficient inquiry-based cell viability experiment using HeLa cells and tools that are readily available in an undergraduate biology laboratory. Students will become familiar with common techniques such as trypsinizing cells, cell counting with a hemocytometer, performing serial dilutions, and determining cell viability using trypan blue dye. Additionally, students will work with graphing software to analyze their data and think critically about the mechanism of death on a cellular level. Two different adaptations of this inquiry-based lab are presented-one for non-biology majors and one for biology majors. Overall, these laboratories aim to expose students to mammalian cell culture and basic techniques and help them to conceptualize their application in scientific research.

Prion potency in stem cells biology.

Science.gov (United States)

Lopes, Marilene H; Santos, Tiago G

2012-01-01

Prion protein (PrP) can be considered a pivotal molecule because it interacts with several partners to perform a diverse range of critical biological functions that might differ in embryonic and adult cells. In recent years, there have been major advances in elucidating the putative role of PrP in the basic biology of stem cells in many different systems. Here, we review the evidence indicating that PrP is a key molecule involved in driving different aspects of the potency of embryonic and tissue-specific stem cells in self-perpetuation and differentiation in many cell types. It has been shown that PrP is involved in stem cell self-renewal, controlling pluripotency gene expression, proliferation, and neural and cardiomyocyte differentiation. PrP also has essential roles in distinct processes that regulate tissue-specific stem cell biology in nervous and hematopoietic systems and during muscle regeneration. Results from our own investigations have shown that PrP is able to modulate self-renewal and proliferation in neural stem cells, processes that are enhanced by PrP interactions with stress inducible protein 1 (STI1). Thus, the available data reveal the influence of PrP in acting upon the maintenance of pluripotent status or the differentiation of stem cells from the early embryogenesis through adulthood.

ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus.

Directory of Open Access Journals (Sweden)

Peter D. Karp

2015-01-01

Full Text Available Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology [ISMB] 2016, Orlando, Florida.

Cell biology experiments conducted in space

Science.gov (United States)

Taylor, G. R.

1977-01-01

A review of cell biology experiments conducted during the first two decades of space flight is provided. References are tabulated for work done with six types of living test system: isolated viruses, bacteriophage-host, bacteria, yeasts and filamentous fungi, protozoans, and small groups of cells (such as hamster cell tissue and fertilized frog eggs). The general results of studies involving the survival of cells in space, the effect of space flight on growing cultures, the biological effects of multicharged high-energy particles, and the effects of space flight on the genetic apparatus of microorganisms are summarized. It is concluded that cell systems remain sufficiently stable during space flight to permit experimentation with models requiring a fixed cell line during the space shuttle era.

iTools: a framework for classification, categorization and integration of computational biology resources.

Directory of Open Access Journals (Sweden)

Ivo D Dinov

2008-05-01

Full Text Available The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long

Cell-free synthetic biology: thinking outside the cell.

Science.gov (United States)

Hodgman, C Eric; Jewett, Michael C

2012-05-01

Cell-free synthetic biology is emerging as a powerful approach aimed to understand, harness, and expand the capabilities of natural biological systems without using intact cells. Cell-free systems bypass cell walls and remove genetic regulation to enable direct access to the inner workings of the cell. The unprecedented level of control and freedom of design, relative to in vivo systems, has inspired the rapid development of engineering foundations for cell-free systems in recent years. These efforts have led to programmed circuits, spatially organized pathways, co-activated catalytic ensembles, rational optimization of synthetic multi-enzyme pathways, and linear scalability from the micro-liter to the 100-liter scale. It is now clear that cell-free systems offer a versatile test-bed for understanding why nature's designs work the way they do and also for enabling biosynthetic routes to novel chemicals, sustainable fuels, and new classes of tunable materials. While challenges remain, the emergence of cell-free systems is poised to open the way to novel products that until now have been impractical, if not impossible, to produce by other means. Copyright © 2011 Elsevier Inc. All rights reserved.

Computational modeling of heterogeneity and function of CD4+ T cells

Directory of Open Access Journals (Sweden)

Adria eCarbo

2014-07-01

Full Text Available The immune system is composed of many different cell types and hundreds of intersecting molecular pathways and signals. This large biological complexity requires coordination between distinct pro-inflammatory and regulatory cell subsets to respond to infection while maintaining tissue homeostasis. CD4+ T cells play a central role in orchestrating immune responses and in maintaining a balance between pro- and anti- inflammatory responses. This tight balance between regulatory and effector reactions depends on the ability of CD4+ T cells to modulate distinct pathways within large molecular networks, since dysregulated CD4+ T cell responses may result in chronic inflammatory and autoimmune diseases. The CD4+ T cell differentiation process comprises an intricate interplay between cytokines, their receptors, adaptor molecules, signaling cascades and transcription factors that help delineate cell fate and function. Computational modeling can help to describe, simulate, analyze, and predict some of the behaviors in this complicated differentiation network. This review provides a comprehensive overview of existing computational immunology methods as well as novel strategies used to model immune responses with a particular focus on CD4+ T cell differentiation.

Elastic Multi-scale Mechanisms: Computation and Biological Evolution.

Science.gov (United States)

Diaz Ochoa, Juan G

2018-01-01

Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.

Biology of Schwann cells.

Science.gov (United States)

Kidd, Grahame J; Ohno, Nobuhiko; Trapp, Bruce D

2013-01-01

The fundamental roles of Schwann cells during peripheral nerve formation and regeneration have been recognized for more than 100 years, but the cellular and molecular mechanisms that integrate Schwann cell and axonal functions continue to be elucidated. Derived from the embryonic neural crest, Schwann cells differentiate into myelinating cells or bundle multiple unmyelinated axons into Remak fibers. Axons dictate which differentiation path Schwann cells follow, and recent studies have established that axonal neuregulin1 signaling via ErbB2/B3 receptors on Schwann cells is essential for Schwann cell myelination. Extracellular matrix production and interactions mediated by specific integrin and dystroglycan complexes are also critical requisites for Schwann cell-axon interactions. Myelination entails expansion and specialization of the Schwann cell plasma membrane over millimeter distances. Many of the myelin-specific proteins have been identified, and transgenic manipulation of myelin genes have provided novel insights into myelin protein function, including maintenance of axonal integrity and survival. Cellular events that facilitate myelination, including microtubule-based protein and mRNA targeting, and actin based locomotion, have also begun to be understood. Arguably, the most remarkable facet of Schwann cell biology, however, is their vigorous response to axonal damage. Degradation of myelin, dedifferentiation, division, production of axonotrophic factors, and remyelination all underpin the substantial regenerative capacity of the Schwann cells and peripheral nerves. Many of these properties are not shared by CNS fibers, which are myelinated by oligodendrocytes. Dissecting the molecular mechanisms responsible for the complex biology of Schwann cells continues to have practical benefits in identifying novel therapeutic targets not only for Schwann cell-specific diseases but other disorders in which axons degenerate. Copyright © 2013 Elsevier B.V. All rights

Chaste: an open source C++ library for computational physiology and biology.

KAUST Repository

Mirams, Gary R; Arthurs, Christopher J; Bernabeu, Miguel O; Bordas, Rafel; Cooper, Jonathan; Corrias, Alberto; Davit, Yohan; Dunn, Sara-Jane; Fletcher, Alexander G; Harvey, Daniel G; Marsh, Megan E; Osborne, James M; Pathmanathan, Pras; Pitt-Francis, Joe; Southern, James; Zemzemi, Nejib; Gavaghan, David J

2013-01-01

Chaste - Cancer, Heart And Soft Tissue Environment - is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to 're-invent the wheel' with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials.

Chaste: an open source C++ library for computational physiology and biology.

Directory of Open Access Journals (Sweden)

Gary R Mirams

Full Text Available Chaste - Cancer, Heart And Soft Tissue Environment - is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs. Re-use of these components avoids the need for researchers to 're-invent the wheel' with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials.

Chaste: an open source C++ library for computational physiology and biology.

KAUST Repository

Mirams, Gary R

2013-03-14

Chaste - Cancer, Heart And Soft Tissue Environment - is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to \\'re-invent the wheel\\' with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials.

Laboratory of Cell and Molecular Biology

Data.gov (United States)

Federal Laboratory Consortium — The Laboratory of Cell and Molecular Biology investigates the organization, compartmentalization, and biochemistry of eukaryotic cells and the pathology associated...

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

Science.gov (United States)

Ross, Muriel D.

1991-01-01

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Computational Biology and the Limits of Shared Vision

DEFF Research Database (Denmark)

Carusi, Annamaria

2011-01-01

of cases is necessary in order to gain a better perspective on social sharing of practices, and on what other factors this sharing is dependent upon. The article presents the case of currently emerging inter-disciplinary visual practices in the domain of computational biology, where the sharing of visual...... practices would be beneficial to the collaborations necessary for the research. Computational biology includes sub-domains where visual practices are coming to be shared across disciplines, and those where this is not occurring, and where the practices of others are resisted. A significant point......, its domain of study. Social practices alone are not sufficient to account for the shaping of evidence. The philosophy of Merleau-Ponty is introduced as providing an alternative framework for thinking of the complex inter-relations between all of these factors. This [End Page 300] philosophy enables us...

Bioconductor: open software development for computational biology and bioinformatics

DEFF Research Database (Denmark)

Gentleman, R.C.; Carey, V.J.; Bates, D.M.

2004-01-01

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisci......The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry...... into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples....

Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

Directory of Open Access Journals (Sweden)

Shuo Gu

2017-01-01

Full Text Available With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective.

Science.gov (United States)

Gu, Shuo; Pei, Jianfeng

2017-01-01

With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

Glycoengineering in CHO cells: Advances in systems biology

DEFF Research Database (Denmark)

Tejwani, Vijay; Andersen, Mikael Rørdam; Nam, Jong Hyun

2018-01-01

are not well understood. A systems biology approach combining different technologies is needed for complete understanding of the molecular processes accounting for this variability and to open up new venues in cell line development. In this review, we describe several advances in genetic manipulation, modeling......For several decades, glycoprotein biologics have been successfully produced from Chinese hamster ovary (CHO) cells. The therapeutic efficacy and potency of glycoprotein biologics are often dictated by their post translational modifications, particularly glycosylation, which unlike protein synthesis....... Recently, CHO cells have also been explored for production of therapeutic glycosaminoglycans (e.g. heparin), which presents similar challenges as producing glycoproteins biologics. Approaches to controlling heterogeneity in CHO cells and directing the biosynthetic process toward desired glycoforms...

XIV Mediterranean Conference on Medical and Biological Engineering and Computing

CERN Document Server

Christofides, Stelios; Pattichis, Constantinos

2016-01-01

This volume presents the proceedings of Medicon 2016, held in Paphos, Cyprus. Medicon 2016 is the XIV in the series of regional meetings of the International Federation of Medical and Biological Engineering (IFMBE) in the Mediterranean. The goal of Medicon 2016 is to provide updated information on the state of the art on Medical and Biological Engineering and Computing under the main theme “Systems Medicine for the Delivery of Better Healthcare Services”. Medical and Biological Engineering and Computing cover complementary disciplines that hold great promise for the advancement of research and development in complex medical and biological systems. Research and development in these areas are impacting the science and technology by advancing fundamental concepts in translational medicine, by helping us understand human physiology and function at multiple levels, by improving tools and techniques for the detection, prevention and treatment of disease. Medicon 2016 provides a common platform for the cross fer...

Development and Implementation of Biological Circuits Using Excitable and Non-Excitable Cells

Energy Technology Data Exchange (ETDEWEB)

Casasnovas-Orus, V.; Gomez-Cid, L.; Hernandez-Romero, I.; Fuentes, L.; Guillem, M.S.; Atienza, F.; Fernandez-Aviles, F.; Climent, A.M.

2016-07-01

Compared to conventional computation systems, living beings require reduced power and raw materials consumption, inviting to explore the concept of biological circuits. In this project, a proof-of-concept of logical biocircuits using cell patterns has been developed. These were based upon differential ionic communication between cells, being the cells types used excitable and non-excitable, modeled by cardiomyocytes and fibroblasts correspondingly. To begin, patterns for the basic logic computation blocks were designed, including the OR gate, AND gate and logic memory. The designs were evaluated with mathematical models and in vitro experiments. Results of mathematical modeling indicated that theoretical approval of the biocircuit function. Regarding in vitro biocircuit implementation, three different selective cell localization techniques proved useful for the pattern creation. Evaluation with optical mapping confirmed the operation of the OR gate and logic memory. More resolution in the cell placement strategy will be needed to observe the proper AND gate operation. Thus, fine-tuning of the implementation process will enable the construction of more complex biocircuits that will take on clinical applications relating to electric stimulation of tissues and programmed drug delivery. (Author)

Lipid Cell Biology: A Focus on Lipids in Cell Division.

Science.gov (United States)

Storck, Elisabeth M; Özbalci, Cagakan; Eggert, Ulrike S

2018-06-20

Cells depend on hugely diverse lipidomes for many functions. The actions and structural integrity of the plasma membrane and most organelles also critically depend on membranes and their lipid components. Despite the biological importance of lipids, our understanding of lipid engagement, especially the roles of lipid hydrophobic alkyl side chains, in key cellular processes is still developing. Emerging research has begun to dissect the importance of lipids in intricate events such as cell division. This review discusses how these structurally diverse biomolecules are spatially and temporally regulated during cell division, with a focus on cytokinesis. We analyze how lipids facilitate changes in cellular morphology during division and how they participate in key signaling events. We identify which cytokinesis proteins are associated with membranes, suggesting lipid interactions. More broadly, we highlight key unaddressed questions in lipid cell biology and techniques, including mass spectrometry, advanced imaging, and chemical biology, which will help us gain insights into the functional roles of lipids.

Concise Review: Stem Cell Population Biology: Insights from Hematopoiesis.

Science.gov (United States)

MacLean, Adam L; Lo Celso, Cristina; Stumpf, Michael P H

2017-01-01

Stem cells are fundamental to human life and offer great therapeutic potential, yet their biology remains incompletely-or in cases even poorly-understood. The field of stem cell biology has grown substantially in recent years due to a combination of experimental and theoretical contributions: the experimental branch of this work provides data in an ever-increasing number of dimensions, while the theoretical branch seeks to determine suitable models of the fundamental stem cell processes that these data describe. The application of population dynamics to biology is amongst the oldest applications of mathematics to biology, and the population dynamics perspective continues to offer much today. Here we describe the impact that such a perspective has made in the field of stem cell biology. Using hematopoietic stem cells as our model system, we discuss the approaches that have been used to study their key properties, such as capacity for self-renewal, differentiation, and cell fate lineage choice. We will also discuss the relevance of population dynamics in models of stem cells and cancer, where competition naturally emerges as an influential factor on the temporal evolution of cell populations. Stem Cells 2017;35:80-88. © 2016 AlphaMed Press.

Two- and three-input TALE-based AND logic computation in embryonic stem cells.

Science.gov (United States)

Lienert, Florian; Torella, Joseph P; Chen, Jan-Hung; Norsworthy, Michael; Richardson, Ryan R; Silver, Pamela A

2013-11-01

Biological computing circuits can enhance our ability to control cellular functions and have potential applications in tissue engineering and medical treatments. Transcriptional activator-like effectors (TALEs) represent attractive components of synthetic gene regulatory circuits, as they can be designed de novo to target a given DNA sequence. We here demonstrate that TALEs can perform Boolean logic computation in mammalian cells. Using a split-intein protein-splicing strategy, we show that a functional TALE can be reconstituted from two inactive parts, thus generating two-input AND logic computation. We further demonstrate three-piece intein splicing in mammalian cells and use it to perform three-input AND computation. Using methods for random as well as targeted insertion of these relatively large genetic circuits, we show that TALE-based logic circuits are functional when integrated into the genome of mouse embryonic stem cells. Comparing construct variants in the same genomic context, we modulated the strength of the TALE-responsive promoter to improve the output of these circuits. Our work establishes split TALEs as a tool for building logic computation with the potential of controlling expression of endogenous genes or transgenes in response to a combination of cellular signals.

Micro/nano-fabrication technologies for cell biology.

Science.gov (United States)

Qian, Tongcheng; Wang, Yingxiao

2010-10-01

Micro/nano-fabrication techniques, such as soft lithography and electrospinning, have been well-developed and widely applied in many research fields in the past decade. Due to the low costs and simple procedures, these techniques have become important and popular for biological studies. In this review, we focus on the studies integrating micro/nano-fabrication work to elucidate the molecular mechanism of signaling transduction in cell biology. We first describe different micro/nano-fabrication technologies, including techniques generating three-dimensional scaffolds for tissue engineering. We then introduce the application of these technologies in manipulating the physical or chemical micro/nano-environment to regulate the cellular behavior and response, such as cell life and death, differentiation, proliferation, and cell migration. Recent advancement in integrating the micro/nano-technologies and live cell imaging are also discussed. Finally, potential schemes in cell biology involving micro/nano-fabrication technologies are proposed to provide perspectives on the future research activities.

Computed tomography of cryogenic cells

International Nuclear Information System (INIS)

Schneider, Gerd; Anderson, E.; Vogt, S.; Knochel, C.; Weiss, D.; LeGros, M.; Larabell, C.

2001-01-01

Due to the short wavelengths of X-rays and low numerical aperture of the Fresnel zone plates used as X-ray objectives, the depth of field is several microns. Within the focal depth, imaging a thick specimen is to a good approximation equivalent to projecting the specimen absorption. Therefore, computed tomography based on a tilt series of X-ray microscopic images can be used to reconstruct the local linear absorption coefficient and image the three-dimensional specimen structure. To preserve the structural integrity of biological objects during image acquisition, microscopy is performed at cryogenic temperatures. Tomography based on X-ray microscopic images was applied to study the distribution of male specific lethal 1 (MSL-1), a nuclear protein involved in dosage compensation in Drosophila melanogaster, which ensures that males with single X chromosome have the same amount of most X-linked gene products as females with two X chromosomes. Tomographic reconstructions of X-ray microscopic images were used to compute the local three-dimensional linear absorption coefficient revealing the arrangement of internal structures of Drosophila melanogaster cells. Combined with labelling techniques, nanotomography is a new technique to study the 3D distribution of selected proteins inside whole cells. We want to improve this technique with respect to resolution and specimen preparation. The resolution in the reconstruction can be significantly improved by reducing the angular step size to collect more viewing angles, which requires an automated data acquisition. In addition, fast-freezing with liquid ethane instead of cryogenic He gas will be applied to improve the vitrification of the hydrated samples. We also plan to apply cryo X-ray nanotomography in order to study different types of cells and their nuclear protein distributions

Systems biology of stored blood cells: can it help to extend the expiration date?

Science.gov (United States)

Paglia, Giuseppe; Palsson, Bernhard Ø; Sigurjonsson, Olafur E

2012-12-05

With increasingly stringent regulations regarding deferral and elimination of blood donors it will become increasingly important to extend the expiration date of blood components beyond the current allowed storage periods. One reason for the storage time limit for blood components is that platelets and red blood cells develop a condition called storage lesions during their storage in plastic blood containers. Systems biology provides comprehensive bio-chemical descriptions of organisms through quantitative measurements and data integration in mathematical models. The biological knowledge for a target organism can be translated in a mathematical format and used to compute physiological properties. The use of systems biology represents a concrete solution in the study of blood cell storage lesions, and it may open up new avenues towards developing better storage methods and better storage media, thereby extending the storage period of blood components. This article is part of a Special Issue entitled: Integrated omics. Copyright © 2012 Elsevier B.V. All rights reserved.

Modeling biological problems in computer science: a case study in genome assembly.

Science.gov (United States)

Medvedev, Paul

2018-01-30

As computer scientists working in bioinformatics/computational biology, we often face the challenge of coming up with an algorithm to answer a biological question. This occurs in many areas, such as variant calling, alignment and assembly. In this tutorial, we use the example of the genome assembly problem to demonstrate how to go from a question in the biological realm to a solution in the computer science realm. We show the modeling process step-by-step, including all the intermediate failed attempts. Please note this is not an introduction to how genome assembly algorithms work and, if treated as such, would be incomplete and unnecessarily long-winded. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Computational properties of mitochondria in T cell activation and fate.

Science.gov (United States)

Uzhachenko, Roman; Shanker, Anil; Dupont, Geneviève

2016-11-01

In this article, we review how mitochondrial Ca 2+ transport (mitochondrial Ca 2+ uptake and Na + /Ca 2+ exchange) is involved in T cell biology, including activation and differentiation through shaping cellular Ca 2+ signals. Based on recent observations, we propose that the Ca 2+ crosstalk between mitochondria, endoplasmic reticulum and cytoplasm may form a proportional-integral-derivative (PID) controller. This PID mechanism (which is well known in engineering) could be responsible for computing cellular decisions. In addition, we point out the importance of analogue and digital signal processing in T cell life and implication of mitochondrial Ca 2+ transport in this process. © 2016 The Authors.

Three-dimensional printing of human skeletal muscle cells: An interdisciplinary approach for studying biological systems.

Science.gov (United States)

Bagley, James R; Galpin, Andrew J

2015-01-01

Interdisciplinary exploration is vital to education in the 21st century. This manuscript outlines an innovative laboratory-based teaching method that combines elements of biochemistry/molecular biology, kinesiology/health science, computer science, and manufacturing engineering to give students the ability to better conceptualize complex biological systems. Here, we utilize technology available at most universities to print three-dimensional (3D) scale models of actual human muscle cells (myofibers) out of bioplastic materials. The same methodological approach could be applied to nearly any cell type or molecular structure. This advancement is significant because historically, two-dimensional (2D) myocellular images have proven insufficient for detailed analysis of organelle organization and morphology. 3D imaging fills this void by providing accurate and quantifiable myofiber structural data. Manipulating tangible 3D models combats 2D limitation and gives students new perspectives and alternative learning experiences that may assist their understanding. This approach also exposes learners to 1) human muscle cell extraction and isolation, 2) targeted fluorescence labeling, 3) confocal microscopy, 4) image processing (via open-source software), and 5) 3D printing bioplastic scale-models (×500 larger than the actual cells). Creating these physical models may further student's interest in the invisible world of molecular and cellular biology. Furthermore, this interdisciplinary laboratory project gives instructors of all biological disciplines a new teaching tool to foster integrative thinking. © 2015 The International Union of Biochemistry and Molecular Biology.

Computational intelligence, medicine and biology selected links

CERN Document Server

Zaitseva, Elena

2015-01-01

This book contains an interesting and state-of the art collection of chapters presenting several examples of attempts to developing modern tools utilizing computational intelligence in different real life problems encountered by humans. Reasoning, prediction, modeling, optimization, decision making, etc. need modern, soft and intelligent algorithms, methods and methodologies to solve, in the efficient ways, problems appearing in human activity. The contents of the book is divided into two parts. Part I, consisting of four chapters, is devoted to selected links of computational intelligence, medicine, health care and biomechanics. Several problems are considered: estimation of healthcare system reliability, classification of ultrasound thyroid images, application of fuzzy logic to measure weight status and central fatness, and deriving kinematics directly from video records. Part II, also consisting of four chapters, is devoted to selected links of computational intelligence and biology. The common denominato...

Using a Computer Animation to Teach High School Molecular Biology

Science.gov (United States)

Rotbain, Yosi; Marbach-Ad, Gili; Stavy, Ruth

2008-01-01

We present an active way to use a computer animation in secondary molecular genetics class. For this purpose we developed an activity booklet that helps students to work interactively with a computer animation which deals with abstract concepts and processes in molecular biology. The achievements of the experimental group were compared with those…

Synthetic biology approaches to engineer T cells.

Science.gov (United States)

Wu, Chia-Yung; Rupp, Levi J; Roybal, Kole T; Lim, Wendell A

2015-08-01

There is rapidly growing interest in learning how to engineer immune cells, such as T lymphocytes, because of the potential of these engineered cells to be used for therapeutic applications such as the recognition and killing of cancer cells. At the same time, our knowhow and capability to logically engineer cellular behavior is growing rapidly with the development of synthetic biology. Here we describe how synthetic biology approaches are being used to rationally alter the behavior of T cells to optimize them for therapeutic functions. We also describe future developments that will be important in order to construct safe and precise T cell therapeutics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Electromagnetic effects - From cell biology to medicine.

Science.gov (United States)

Funk, Richard H W; Monsees, Thomas; Ozkucur, Nurdan

2009-01-01

In this review we compile and discuss the published plethora of cell biological effects which are ascribed to electric fields (EF), magnetic fields (MF) and electromagnetic fields (EMF). In recent years, a change in paradigm took place concerning the endogenously produced static EF of cells and tissues. Here, modern molecular biology could link the action of ion transporters and ion channels to the "electric" action of cells and tissues. Also, sensing of these mainly EF could be demonstrated in studies of cell migration and wound healing. The triggers exerted by ion concentrations and concomitant electric field gradients have been traced along signaling cascades till gene expression changes in the nucleus. Far more enigmatic is the way of action of static MF which come in most cases from outside (e.g. earth magnetic field). All systems in an organism from the molecular to the organ level are more or less in motion. Thus, in living tissue we mostly find alternating fields as well as combination of EF and MF normally in the range of extremely low-frequency EMF. Because a bewildering array of model systems and clinical devices exits in the EMF field we concentrate on cell biological findings and look for basic principles in the EF, MF and EMF action. As an outlook for future research topics, this review tries to link areas of EF, MF and EMF research to thermodynamics and quantum physics, approaches that will produce novel insights into cell biology.

An experimental and computational framework to build a dynamic protein atlas of human cell division

OpenAIRE

Kavur, Marina; Kavur, Marina; Kavur, Marina; Ellenberg, Jan; Peters, Jan-Michael; Ladurner, Rene; Martinic, Marina; Kueblbeck, Moritz; Nijmeijer, Bianca; Wachsmuth, Malte; Koch, Birgit; Walther, Nike; Politi, Antonio; Heriche, Jean-Karim; Hossain, M.

2017-01-01

Essential biological functions of human cells, such as division, require the tight coordination of the activity of hundreds of proteins in space and time. While live cell imaging is a powerful tool to study the distribution and dynamics of individual proteins after fluorescence tagging, it has not yet been used to map protein networks due to the lack of systematic and quantitative experimental and computational approaches. Using the cell and nuclear boundaries as landmarks, we generated a 4D ...

Seeing Cells: Teaching the Visual/Verbal Rhetoric of Biology

Science.gov (United States)

Dinolfo, John; Heifferon, Barbara; Temesvari, Lesly A.

2007-01-01

This pilot study obtained baseline information on verbal and visual rhetorics to teach microscopy techniques to college biology majors. We presented cell images to students in cell biology and biology writing classes and then asked them to identify textual, verbal, and visual cues that support microscopy learning. Survey responses suggest that…

Mammalian cell biology

International Nuclear Information System (INIS)

Anon.

1976-01-01

Progress is reported on studies of the molecular biology and functional changes in cultured mammalian cells following exposure to x radiation, uv radiation, fission neutrons, or various chemical environmental pollutants alone or in combinations. Emphasis was placed on the separate and combined effects of polycyclic aromatic hydrocarbons released during combustion of fossil fuels and ionizing and nonionizing radiations. Sun lamps, which emit a continuous spectrum of near ultraviolet light of 290 nm to 315 nm were used for studies of predictive cell killing due to sunlight. Results showed that exposure to uv light (254 nm) may not be adequate to predict effects produced by sunlight. Data are included from studies on single-strand breaks and repair in DNA of cultured hamster cells exposed to uv or nearultraviolet light. The possible interactions of the polycyclic aromatic hydrocarbon 7,12-dimethylbenz(a)-anthracene (DmBA) alone or combined with exposure to x radiation, uv radiation (254 nm) or near ultraviolet simulating sunlight were compared for effects on cell survival

Cell biology of the Koji mold Aspergillus oryzae.

Science.gov (United States)

Kitamoto, Katsuhiko

2015-01-01

Koji mold, Aspergillus oryzae, has been used for the production of sake, miso, and soy sauce for more than one thousand years in Japan. Due to the importance, A. oryzae has been designated as the national micro-organism of Japan (Koku-kin). A. oryzae has been intensively studied in the past century, with most investigations focusing on breeding techniques and developing methods for Koji making for sake brewing. However, the understanding of fundamental biology of A. oryzae remains relatively limited compared with the yeast Saccharomyces cerevisiae. Therefore, we have focused on studying the cell biology including live cell imaging of organelles, protein vesicular trafficking, autophagy, and Woronin body functions using the available genomic information. In this review, I describe essential findings of cell biology of A. oryzae obtained in our study for a quarter of century. Understanding of the basic biology will be critical for not its biotechnological application, but also for an understanding of the fundamental biology of other filamentous fungi.

Potentials of single-cell biology in identification and validation of disease biomarkers.

Science.gov (United States)

Niu, Furong; Wang, Diane C; Lu, Jiapei; Wu, Wei; Wang, Xiangdong

2016-09-01

Single-cell biology is considered a new approach to identify and validate disease-specific biomarkers. However, the concern raised by clinicians is how to apply single-cell measurements for clinical practice, translate the message of single-cell systems biology into clinical phenotype or explain alterations of single-cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single-cell gene sequencing in the identification and development of disease-specific biomarkers, the definition and significance of single-cell biology and single-cell systems biology in the understanding of single-cell full picture, the development and establishment of whole-cell models in the validation of targeted biological function and the figure and meaning of single-molecule imaging in single cell to trace intra-single-cell molecule expression, signal, interaction and location. We headline the important role of single-cell biology in the discovery and development of disease-specific biomarkers with a special emphasis on understanding single-cell biological functions, e.g. mechanical phenotypes, single-cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi-dimensional, multi-layer, multi-crossing and stereoscopic single-cell biology definitely benefits the discovery and development of disease-specific biomarkers. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Tomography studies of biological cells on polymer scaffolds

International Nuclear Information System (INIS)

Thurner, P; Mueller, B; Sennhauser, U; Hubbell, J; Mueller, R

2004-01-01

Advances in cell biology and tissue engineering rely heavily on performing 2D cell culture experiments. Analysis of these is conventionally done with 2D imaging techniques such as light (LM) or electron microscopy (SEM), since they are readily available. Cells, however, might act significantly differently when cultured in 2D or 3D environments. In order to analyse cells in a 3D arrangement, new imaging techniques are necessary not only in order to visualize the periphery of the cell culture in reflection mode but also to perform qualitative and quantitative investigations of the inner parts. Synchrotron radiation micro-computed tomography (SRμCT) using hard x-rays was shown to be a promising tool that can be used for 3D cell culture visualization. SRμCT allows not only visualization of cell cultures in their native 3D environment but also use of the volumetric nature of this imaging procedure to evaluate the cells quantitatively. In our approach, cells were seeded on polymer yarns, stained and measured with SRμCT in absorption and in differential absorption contrast mode. A new segmentation procedure was developed and the measured volumetric data were quantitatively assessed. Quantification parameters included total cell volume, total yarn volume, cell volume density, which is the ratio of cell to yarn volume, and the radial cell mass distribution. The applied variation of the staining parameter of gold enhancement incubation time was shown to have significant influence on the cell volume density. Differential absorption contrast mode was found to provide similar but no additional information on the investigated sample. Using novel approaches of hierarchical volumetric imaging allows closure of the gap between imaging of whole organs and single cells and might be expanded to even higher resolutions, offering investigation of the cell machinery in closer detail

Molecular biology of the cell

National Research Council Canada - National Science Library

Alberts, Bruce; Walter, Peter; Raff, Martin; Roberts, Keith; Lewis, Julian; Johnson, Alexander

2007-01-01

.... By extracting fundamental concepts and meaning from this enormous and ever-growing field, the authors tell the story of cell biology, and create a coherent framework through which non-expert readers...

A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

Science.gov (United States)

2010-01-01

Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological

A comparative approach for the investigation of biological information processing: an examination of the structure and function of computer hard drives and DNA.

Science.gov (United States)

D'Onofrio, David J; An, Gary

2010-01-21

The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an

A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

Directory of Open Access Journals (Sweden)

D'Onofrio David J

2010-01-01

Full Text Available Abstract Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1 orthogonal uniqueness, (2 low level formatting, (3 high level formatting and (4 translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT during high level formatting of the computer hard drive and the subsequent loading of an operating

Cell-free synthetic biology for environmental sensing and remediation.

Science.gov (United States)

Karig, David K

2017-06-01

The fields of biosensing and bioremediation leverage the phenomenal array of sensing and metabolic capabilities offered by natural microbes. Synthetic biology provides tools for transforming these fields through complex integration of natural and novel biological components to achieve sophisticated sensing, regulation, and metabolic function. However, the majority of synthetic biology efforts are conducted in living cells, and concerns over releasing genetically modified organisms constitute a key barrier to environmental applications. Cell-free protein expression systems offer a path towards leveraging synthetic biology, while preventing the spread of engineered organisms in nature. Recent efforts in the areas of cell-free approaches for sensing, regulation, and metabolic pathway implementation, as well as for preserving and deploying cell-free expression components, embody key steps towards realizing the potential of cell-free systems for environmental sensing and remediation. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

Biological interaction of living cells with COSAN-based synthetic vesicles.

Science.gov (United States)

Tarrés, Màrius; Canetta, Elisabetta; Paul, Eleanor; Forbes, Jordan; Azzouni, Karima; Viñas, Clara; Teixidor, Francesc; Harwood, Adrian J

2015-01-15

Cobaltabisdicarbollide (COSAN) [3,3'-Co(1,2-C2B9H11)2](-), is a complex boron-based anion that has the unusual property of self-assembly into membranes and vesicles. These membranes have similar dimensions to biological membranes found in cells, and previously COSAN has been shown to pass through synthetic lipid membranes and those of living cells without causing breakdown of membrane barrier properties. Here, we investigate the interaction of this inorganic membrane system with living cells. We show that COSAN has no immediate effect on cell viability, and cells fully recover when COSAN is removed following exposure for hours to days. COSAN elicits a range of cell biological effects, including altered cell morphology, inhibition of cell growth and, in some cases, apoptosis. These observations reveal a new biology at the interface between inorganic, synthetic COSAN membranes and naturally occurring biological membranes.

A computational approach for inferring the cell wall properties that govern guard cell dynamics.

Science.gov (United States)

Woolfenden, Hugh C; Bourdais, Gildas; Kopischke, Michaela; Miedes, Eva; Molina, Antonio; Robatzek, Silke; Morris, Richard J

2017-10-01

Guard cells dynamically adjust their shape in order to regulate photosynthetic gas exchange, respiration rates and defend against pathogen entry. Cell shape changes are determined by the interplay of cell wall material properties and turgor pressure. To investigate this relationship between turgor pressure, cell wall properties and cell shape, we focused on kidney-shaped stomata and developed a biomechanical model of a guard cell pair. Treating the cell wall as a composite of the pectin-rich cell wall matrix embedded with cellulose microfibrils, we show that strong, circumferentially oriented fibres are critical for opening. We find that the opening dynamics are dictated by the mechanical stress response of the cell wall matrix, and as the turgor rises, the pectinaceous matrix stiffens. We validate these predictions with stomatal opening experiments in selected Arabidopsis cell wall mutants. Thus, using a computational framework that combines a 3D biomechanical model with parameter optimization, we demonstrate how to exploit subtle shape changes to infer cell wall material properties. Our findings reveal that proper stomatal dynamics are built on two key properties of the cell wall, namely anisotropy in the form of hoop reinforcement and strain stiffening. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd and Society for Experimental Biology.

Simulation of CNT-AFM tip based on finite element analysis for targeted probe of the biological cell

Energy Technology Data Exchange (ETDEWEB)

Yousefi, Amin Termeh, E-mail: at.tyousefi@gmail.com; Miyake, Mikio, E-mail: miyakejaist@gmail.com; Ikeda, Shoichiro, E-mail: sho16.ikeda@gmail.com [ChECA IKohza, Dept. Environmental & Green Technology (EGT), Malaysia, Japan International Institute of Technology (MJIIT), University Technology Malaysia - UTM, Kualalumpur (Malaysia); Mahmood, Mohamad Rusop, E-mail: nano@uitm.gmail.com [NANO-SciTech Centre, Institute of Science, Universiti Teknologi MARA (UiTM), Shah Alam, Selangor (Malaysia)

2016-07-06

Carbon nanotubes (CNTs) are potentially ideal tips for atomic force microscopy (AFM) due to the robust mechanical properties, nano scale diameter and also their ability to be functionalized by chemical and biological components at the tip ends. This contribution develops the idea of using CNTs as an AFM tip in computational analysis of the biological cell’s. Finite element analysis employed for each section and displacement of the nodes located in the contact area was monitored by using an output database (ODB). This reliable integration of CNT-AFM tip process provides a new class of high performance nanoprobes for single biological cell analysis.

Stochastic processes in cell biology

CERN Document Server

Bressloff, Paul C

2014-01-01

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.  A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods.   This text is primarily...

Filling the gap between biology and computer science.

Science.gov (United States)

Aguilar-Ruiz, Jesús S; Moore, Jason H; Ritchie, Marylyn D

2008-07-17

This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful knowledge from heterogeneous biological data. We outline the aims and scope of the journal, introduce the publishing model and describe the open peer review policy, which fosters interaction within the research community.

Mast cells: potential positive and negative roles in tumor biology.

Science.gov (United States)

Marichal, Thomas; Tsai, Mindy; Galli, Stephen J

2013-11-01

Mast cells are immune cells that reside in virtually all vascularized tissues. Upon activation by diverse mechanisms, mast cells can secrete a broad array of biologically active products that either are stored in the cytoplasmic granules of the cells (e.g., histamine, heparin, various proteases) or are produced de novo upon cell stimulation (e.g., prostaglandins, leukotrienes, cytokines, chemokines, and growth factors). Mast cells are best known for their effector functions during anaphylaxis and acute IgE-associated allergic reactions, but they also have been implicated in a wide variety of processes that maintain health or contribute to disease. There has been particular interest in the possible roles of mast cells in tumor biology. In vitro studies have shown that mast cells have the potential to influence many aspects of tumor biology, including tumor development, tumor-induced angiogenesis, and tissue remodeling, and the shaping of adaptive immune responses to tumors. Yet, the actual contributions of mast cells to tumor biology in vivo remain controversial. Here, we review some basic features of mast cell biology with a special emphasis on those relevant to their potential roles in tumors. We discuss how using in vivo tumor models in combination with models in which mast cell function can be modulated has implicated mast cells in the regulation of host responses to tumors. Finally, we summarize data from studies of human tumors that suggest either beneficial or detrimental roles for mast cells in tumors. ©2013 AACR.

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology

Science.gov (United States)

RUBENSTEIN, MICHAEL; SAI, YING; CHUONG, CHENG-MING; SHEN, WEI-MIN

2010-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. “Self” here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering. PMID:19557691

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology.

Science.gov (United States)

Rubenstein, Michael; Sai, Ying; Chuong, Cheng-Ming; Shen, Wei-Min

2009-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. Self here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering.

MACBenAbim: A Multi-platform Mobile Application for searching keyterms in Computational Biology and Bioinformatics.

Science.gov (United States)

Oluwagbemi, Olugbenga O; Adewumi, Adewole; Esuruoso, Abimbola

2012-01-01

Computational biology and bioinformatics are gradually gaining grounds in Africa and other developing nations of the world. However, in these countries, some of the challenges of computational biology and bioinformatics education are inadequate infrastructures, and lack of readily-available complementary and motivational tools to support learning as well as research. This has lowered the morale of many promising undergraduates, postgraduates and researchers from aspiring to undertake future study in these fields. In this paper, we developed and described MACBenAbim (Multi-platform Mobile Application for Computational Biology and Bioinformatics), a flexible user-friendly tool to search for, define and describe the meanings of keyterms in computational biology and bioinformatics, thus expanding the frontiers of knowledge of the users. This tool also has the capability of achieving visualization of results on a mobile multi-platform context. MACBenAbim is available from the authors for non-commercial purposes.

Mesangial cell biology

Energy Technology Data Exchange (ETDEWEB)

Abboud, Hanna E., E-mail: Abboud@uthscsa.edu

2012-05-15

Mesangial cells originate from the metanephric mesenchyme and maintain structural integrity of the glomerular microvascular bed and mesangial matrix homeostasis. In response to metabolic, immunologic or hemodynamic injury, these cells undergo apoptosis or acquire an activated phenotype and undergo hypertrophy, proliferation with excessive production of matrix proteins, growth factors, chemokines and cytokines. These soluble factors exert autocrine and paracrine effects on the cells or on other glomerular cells, respectively. MCs are primary targets of immune-mediated glomerular diseases such as IGA nephropathy or metabolic diseases such as diabetes. MCs may also respond to injury that primarily involves podocytes and endothelial cells or to structural and genetic abnormalities of the glomerular basement membrane. Signal transduction and oxidant stress pathways are activated in MCs and likely represent integrated input from multiple mediators. Such responses are convenient targets for therapeutic intervention. Studies in cultured MCs should be supplemented with in vivo studies as well as examination of freshly isolated cells from normal and diseases glomeruli. In addition to ex vivo morphologic studies in kidney cortex, cells should be studied in their natural environment, isolated glomeruli or even tissue slices. Identification of a specific marker of MCs should help genetic manipulation as well as selective therapeutic targeting of these cells. Identification of biological responses of MCs that are not mediated by the renin–angiotensin system should help development of novel and effective therapeutic strategies to treat diseases characterized by MC pathology.

Mesangial cell biology

International Nuclear Information System (INIS)

Abboud, Hanna E.

2012-01-01

Mesangial cells originate from the metanephric mesenchyme and maintain structural integrity of the glomerular microvascular bed and mesangial matrix homeostasis. In response to metabolic, immunologic or hemodynamic injury, these cells undergo apoptosis or acquire an activated phenotype and undergo hypertrophy, proliferation with excessive production of matrix proteins, growth factors, chemokines and cytokines. These soluble factors exert autocrine and paracrine effects on the cells or on other glomerular cells, respectively. MCs are primary targets of immune-mediated glomerular diseases such as IGA nephropathy or metabolic diseases such as diabetes. MCs may also respond to injury that primarily involves podocytes and endothelial cells or to structural and genetic abnormalities of the glomerular basement membrane. Signal transduction and oxidant stress pathways are activated in MCs and likely represent integrated input from multiple mediators. Such responses are convenient targets for therapeutic intervention. Studies in cultured MCs should be supplemented with in vivo studies as well as examination of freshly isolated cells from normal and diseases glomeruli. In addition to ex vivo morphologic studies in kidney cortex, cells should be studied in their natural environment, isolated glomeruli or even tissue slices. Identification of a specific marker of MCs should help genetic manipulation as well as selective therapeutic targeting of these cells. Identification of biological responses of MCs that are not mediated by the renin–angiotensin system should help development of novel and effective therapeutic strategies to treat diseases characterized by MC pathology.

7th World Congress on Nature and Biologically Inspired Computing

CERN Document Server

Engelbrecht, Andries; Abraham, Ajith; Plessis, Mathys; Snášel, Václav; Muda, Azah

2016-01-01

World Congress on Nature and Biologically Inspired Computing (NaBIC) is organized to discuss the state-of-the-art as well as to address various issues with respect to Nurturing Intelligent Computing Towards Advancement of Machine Intelligence. This Volume contains the papers presented in the Seventh World Congress (NaBIC’15) held in Pietermaritzburg, South Africa during December 01-03, 2015. The 39 papers presented in this Volume were carefully reviewed and selected. The Volume would be a valuable reference to researchers, students and practitioners in the computational intelligence field.

Quantitative stem cell biology: the threat and the glory.

Science.gov (United States)

Pollard, Steven M

2016-11-15

Major technological innovations over the past decade have transformed our ability to extract quantitative data from biological systems at an unprecedented scale and resolution. These quantitative methods and associated large datasets should lead to an exciting new phase of discovery across many areas of biology. However, there is a clear threat: will we drown in these rivers of data? On 18th July 2016, stem cell biologists gathered in Cambridge for the 5th annual Cambridge Stem Cell Symposium to discuss 'Quantitative stem cell biology: from molecules to models'. This Meeting Review provides a summary of the data presented by each speaker, with a focus on quantitative techniques and the new biological insights that are emerging. © 2016. Published by The Company of Biologists Ltd.

Inter-level relations in computer science, biology, and psychology

NARCIS (Netherlands)

Boogerd, Fred; Bruggeman, Frank; Jonker, Catholijn; Looren de Jong, Huib; Tamminga, Allard; Treur, Jan; Westerhoff, Hans; Wijngaards, Wouter

2002-01-01

Investigations into inter-level relations in computer science, biology and psychology call for an *empirical* turn in the philosophy of mind. Rather than concentrate on *a priori* discussions of inter-level relations between “completed” sciences, a case is made for the actual study of the way

Inter-level relations in computer science, biology, and psychology

NARCIS (Netherlands)

Boogerd, F.; Bruggeman, F.; Jonker, C.M.; Looren de Jong, H.; Tamminga, A.; Treur, J.; Westerhoff, H.V.; Wijngaards, W.C.A.

2002-01-01

Investigations into inter-level relations in computer science, biology and psychology call for an empirical turn in the philosophy of mind. Rather than concentrate on a priori discussions of inter-level relations between 'completed' sciences, a case is made for the actual study of the way

Inter-level relations in computer science, biology and psychology

NARCIS (Netherlands)

Boogerd, F.C.; Bruggeman, F.J.; Jonker, C.M.; Looren De Jong, H.; Tamminga, A.M.; Treur, J.; Westerhoff, H.V.; Wijngaards, W.C.A.

2002-01-01

Investigations into inter-level relations in computer science, biology and psychology call for an empirical turn in the philosophy of mind. Rather than concentrate on a priori discussions of inter-level relations between "completed" sciences, a case is made for the actual study of the way

Application of computational systems biology to explore environmental toxicity hazards

DEFF Research Database (Denmark)

Audouze, Karine Marie Laure; Grandjean, Philippe

2011-01-01

Background: Computer-based modeling is part of a new approach to predictive toxicology.Objectives: We investigated the usefulness of an integrated computational systems biology approach in a case study involving the isomers and metabolites of the pesticide dichlorodiphenyltrichloroethane (DDT......) to ascertain their possible links to relevant adverse effects.Methods: We extracted chemical-protein association networks for each DDT isomer and its metabolites using ChemProt, a disease chemical biology database that includes both binding and gene expression data, and we explored protein-protein interactions...... using a human interactome network. To identify associated dysfunctions and diseases, we integrated protein-disease annotations into the protein complexes using the Online Mendelian Inheritance in Man database and the Comparative Toxicogenomics Database.Results: We found 175 human proteins linked to p,p´-DDT...

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

Science.gov (United States)

Somogyi, Endre; Glazier, James A

2017-04-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

Computing chemical organizations in biological networks.

Science.gov (United States)

Centler, Florian; Kaleta, Christoph; di Fenizio, Pietro Speroni; Dittrich, Peter

2008-07-15

Novel techniques are required to analyze computational models of intracellular processes as they increase steadily in size and complexity. The theory of chemical organizations has recently been introduced as such a technique that links the topology of biochemical reaction network models to their dynamical repertoire. The network is decomposed into algebraically closed and self-maintaining subnetworks called organizations. They form a hierarchy representing all feasible system states including all steady states. We present three algorithms to compute the hierarchy of organizations for network models provided in SBML format. Two of them compute the complete organization hierarchy, while the third one uses heuristics to obtain a subset of all organizations for large models. While the constructive approach computes the hierarchy starting from the smallest organization in a bottom-up fashion, the flux-based approach employs self-maintaining flux distributions to determine organizations. A runtime comparison on 16 different network models of natural systems showed that none of the two exhaustive algorithms is superior in all cases. Studying a 'genome-scale' network model with 762 species and 1193 reactions, we demonstrate how the organization hierarchy helps to uncover the model structure and allows to evaluate the model's quality, for example by detecting components and subsystems of the model whose maintenance is not explained by the model. All data and a Java implementation that plugs into the Systems Biology Workbench is available from http://www.minet.uni-jena.de/csb/prj/ot/tools.

Analog synthetic biology.

Science.gov (United States)

Sarpeshkar, R

2014-03-28

We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog-digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA-protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations.

Where mathematics, computer science, linguistics and biology meet essays in honour of Gheorghe Păun

CERN Document Server

Mitrana, Victor

2001-01-01

In the last years, it was observed an increasing interest of computer scientists in the structure of biological molecules and the way how they can be manipulated in vitro in order to define theoretical models of computation based on genetic engineering tools. Along the same lines, a parallel interest is growing regarding the process of evolution of living organisms. Much of the current data for genomes are expressed in the form of maps which are now becoming available and permit the study of the evolution of organisms at the scale of genome for the first time. On the other hand, there is an active trend nowadays throughout the field of computational biology toward abstracted, hierarchical views of biological sequences, which is very much in the spirit of computational linguistics. In the last decades, results and methods in the field of formal language theory that might be applied to the description of biological sequences were pointed out.

Noninvasive Assessment of Cell Fate and Biology in Transplanted Mesenchymal Stem Cells.

Science.gov (United States)

Franchi, Federico; Rodriguez-Porcel, Martin

2017-01-01

Recently, molecular imaging has become a conditio sine qua non for cell-based regenerative medicine. Developments in molecular imaging techniques, such as reporter gene technology, have increasingly enabled the noninvasive assessment of the fate and biology of cells after cardiovascular applications. In this context, bioluminescence imaging is the most commonly used imaging modality in small animal models of preclinical studies. Here, we present a detailed protocol of a reporter gene imaging approach for monitoring the viability and biology of Mesenchymal Stem Cells transplanted in a mouse model of myocardial ischemia reperfusion injury.

Identifying niche-mediated regulatory factors of stem cell phenotypic state: a systems biology approach.

Science.gov (United States)

Ravichandran, Srikanth; Del Sol, Antonio

2017-02-01

Understanding how the cellular niche controls the stem cell phenotype is often hampered due to the complexity of variegated niche composition, its dynamics, and nonlinear stem cell-niche interactions. Here, we propose a systems biology view that considers stem cell-niche interactions as a many-body problem amenable to simplification by the concept of mean field approximation. This enables approximation of the niche effect on stem cells as a constant field that induces sustained activation/inhibition of specific stem cell signaling pathways in all stem cells within heterogeneous populations exhibiting the same phenotype (niche determinants). This view offers a new basis for the development of single cell-based computational approaches for identifying niche determinants, which has potential applications in regenerative medicine and tissue engineering. © 2017 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Biology Students Building Computer Simulations Using StarLogo TNG

Science.gov (United States)

Smith, V. Anne; Duncan, Ishbel

2011-01-01

Confidence is an important issue for biology students in handling computational concepts. This paper describes a practical in which honours-level bioscience students simulate complex animal behaviour using StarLogo TNG, a freely-available graphical programming environment. The practical consists of two sessions, the first of which guides students…

The cell biology of T-dependent B cell activation

DEFF Research Database (Denmark)

Owens, T; Zeine, R

1989-01-01

The requirement that CD4+ helper T cells recognize antigen in association with class II Major Histocompatibility Complex (MHC) encoded molecules constrains T cells to activation through intercellular interaction. The cell biology of the interactions between CD4+ T cells and antigen-presenting cells...... includes multipoint intermolecular interactions that probably involve aggregation of both polymorphic and monomorphic T cell surface molecules. Such aggregations have been shown in vitro to markedly enhance and, in some cases, induce T cell activation. The production of T-derived lymphokines that have been...... implicated in B cell activation is dependent on the T cell receptor for antigen and its associated CD3 signalling complex. T-dependent help for B cell activation is therefore similarly MHC-restricted and involves T-B intercellular interaction. Recent reports that describe antigen-independent B cell...

Community-driven computational biology with Debian Linux.

Science.gov (United States)

Möller, Steffen; Krabbenhöft, Hajo Nils; Tille, Andreas; Paleino, David; Williams, Alan; Wolstencroft, Katy; Goble, Carole; Holland, Richard; Belhachemi, Dominique; Plessy, Charles

2010-12-21

The Open Source movement and its technologies are popular in the bioinformatics community because they provide freely available tools and resources for research. In order to feed the steady demand for updates on software and associated data, a service infrastructure is required for sharing and providing these tools to heterogeneous computing environments. The Debian Med initiative provides ready and coherent software packages for medical informatics and bioinformatics. These packages can be used together in Taverna workflows via the UseCase plugin to manage execution on local or remote machines. If such packages are available in cloud computing environments, the underlying hardware and the analysis pipelines can be shared along with the software. Debian Med closes the gap between developers and users. It provides a simple method for offering new releases of software and data resources, thus provisioning a local infrastructure for computational biology. For geographically distributed teams it can ensure they are working on the same versions of tools, in the same conditions. This contributes to the world-wide networking of researchers.

A Computational Framework for Bioimaging Simulation

Science.gov (United States)

Watabe, Masaki; Arjunan, Satya N. V.; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units. PMID:26147508

A Computational Framework for Bioimaging Simulation.

Science.gov (United States)

Watabe, Masaki; Arjunan, Satya N V; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

A Computational Framework for Bioimaging Simulation.

Directory of Open Access Journals (Sweden)

Masaki Watabe

Full Text Available Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

Automatic detection of biological cells

International Nuclear Information System (INIS)

Alves Da Costa, Caiuby

1983-01-01

The present research work has dealt with the analysis of biological cell images in general, and more specially with the cervical cells. This work was carried out in order to develop an automaton leading to a better prevention of cancer through automated mass screening. The device has been implemented on Motorola 68.000 microprocessor system. The automaton carries out cell nucleus analysis in several steps. The main steps are: - First: the automaton focuses on an individual cell nucleus among the smear's cell (about 10.000), - Second: it process each nucleus image. The digital processing yields geometrical of the nucleus (area and perimeter) for each cell. These data are stored in a local memory for further discriminant analysis by a microcomputer. In this way smears are classed in two groups: hale smears and uncertain smears. The automaton uses a wired logic for image acquisition and its software algorithms provide image reconstruction. The reconstruction algorithms are general purpose. Tests have proved that they can reconstruct any two dimensional images independently of its geometrical form. Moreover they can make the reconstruction of any image among the several images present in observation field. The processing times registered during the tests (for different cases) were situated, all of them, below three minutes for 10,000 images (each of them formed by an average of 450 pixels). The interest of the method is generality and speed. The only restriction is the primary device sensor (CCD linear array) length. Thus the automaton application can be extended beyond the biological image field. (author) [fr

A Diagnostic Assessment for Introductory Molecular and Cell Biology

Science.gov (United States)

Shi, Jia; Wood, William B.; Martin, Jennifer M.; Guild, Nancy A.; Vicens, Quentin; Knight, Jennifer K.

2010-01-01

We have developed and validated a tool for assessing understanding of a selection of fundamental concepts and basic knowledge in undergraduate introductory molecular and cell biology, focusing on areas in which students often have misconceptions. This multiple-choice Introductory Molecular and Cell Biology Assessment (IMCA) instrument is designed…

Glial cell biology in the Great Lakes region.

Science.gov (United States)

Feinstein, Douglas L; Skoff, Robert P

2016-03-31

We report on the tenth bi-annual Great Lakes Glial meeting, held in Traverse City, Michigan, USA, September 27-29 2015. The GLG meeting is a small conference that focuses on current research in glial cell biology. The array of functions that glial cells (astrocytes, microglia, oligodendrocytes, Schwann cells) play in health and disease is constantly increasing. Despite this diversity, GLG meetings bring together scientists with common interests, leading to a better understanding of these cells. This year's meeting included two keynote speakers who presented talks on the regulation of CNS myelination and the consequences of stress on Schwann cell biology. Twenty-two other talks were presented along with two poster sessions. Sessions covered recent findings in the areas of microglial and astrocyte activation; age-dependent changes to glial cells, Schwann cell development and pathology, and the role of stem cells in glioma and neural regeneration.

The synergistic use of computation, chemistry and biology to discover novel peptide-based drugs: the time is right.

Science.gov (United States)

Audie, J; Boyd, C

2010-01-01

The case for peptide-based drugs is compelling. Due to their chemical, physical and conformational diversity, and relatively unproblematic toxicity and immunogenicity, peptides represent excellent starting material for drug discovery. Nature has solved many physiological and pharmacological problems through the use of peptides, polypeptides and proteins. If nature could solve such a diversity of challenging biological problems through the use of peptides, it seems reasonable to infer that human ingenuity will prove even more successful. And this, indeed, appears to be the case, as a number of scientific and methodological advances are making peptides and peptide-based compounds ever more promising pharmacological agents. Chief among these advances are powerful chemical and biological screening technologies for lead identification and optimization, methods for enhancing peptide in vivo stability, bioavailability and cell-permeability, and new delivery technologies. Other advances include the development and experimental validation of robust computational methods for peptide lead identification and optimization. Finally, scientific analysis, biology and chemistry indicate the prospect of designing relatively small peptides to therapeutically modulate so-called 'undruggable' protein-protein interactions. Taken together a clear picture is emerging: through the synergistic use of the scientific imagination and the computational, chemical and biological methods that are currently available, effective peptide therapeutics for novel targets can be designed that surpass even the proven peptidic designs of nature.

Molecular biology of mycoplasmas: from the minimum cell concept to the artificial cell.

Science.gov (United States)

Cordova, Caio M M; Hoeltgebaum, Daniela L; Machado, Laís D P N; Santos, Larissa Dos

2016-01-01

Mycoplasmas are a large group of bacteria, sorted into different genera in the Mollicutes class, whose main characteristic in common, besides the small genome, is the absence of cell wall. They are considered cellular and molecular biology study models. We present an updated review of the molecular biology of these model microorganisms and the development of replicative vectors for the transformation of mycoplasmas. Synthetic biology studies inspired by these pioneering works became possible and won the attention of the mainstream media. For the first time, an artificial genome was synthesized (a minimal genome produced from consensus sequences obtained from mycoplasmas). For the first time, a functional artificial cell has been constructed by introducing a genome completely synthesized within a cell envelope of a mycoplasma obtained by transformation techniques. Therefore, this article offers an updated insight to the state of the art of these peculiar organisms' molecular biology.

METABOLIC MODELLING IN THE DEVELOPMENT OF CELL FACTORIES BY SYNTHETIC BIOLOGY

Directory of Open Access Journals (Sweden)

Paula Jouhten

2012-10-01

Full Text Available Cell factories are commonly microbial organisms utilized for bioconversion of renewable resources to bulk or high value chemicals. Introduction of novel production pathways in chassis strains is the core of the development of cell factories by synthetic biology. Synthetic biology aims to create novel biological functions and systems not found in nature by combining biology with engineering. The workflow of the development of novel cell factories with synthetic biology is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow. In this minireview, the role of metabolic modelling in synthetic biology will be discussed with a review of current status of compatible methods and models for the in silico design and quantitative evaluation of a cell factory.

Integrative systems and synthetic biology of cell-matrix adhesion sites.

Science.gov (United States)

Zamir, Eli

2016-09-02

The complexity of cell-matrix adhesion convolves its roles in the development and functioning of multicellular organisms and their evolutionary tinkering. Cell-matrix adhesion is mediated by sites along the plasma membrane that anchor the actin cytoskeleton to the matrix via a large number of proteins, collectively called the integrin adhesome. Fundamental challenges for understanding how cell-matrix adhesion sites assemble and function arise from their multi-functionality, rapid dynamics, large number of components and molecular diversity. Systems biology faces these challenges in its strive to understand how the integrin adhesome gives rise to functional adhesion sites. Synthetic biology enables engineering intracellular modules and circuits with properties of interest. In this review I discuss some of the fundamental questions in systems biology of cell-matrix adhesion and how synthetic biology can help addressing them.

The transhumanism of Ray Kurzweil. Is biological ontology reducible to computation?

Directory of Open Access Journals (Sweden)

Javier Monserrat

2016-02-01

Full Text Available Computer programs, primarily engineering machine vision and programming of somatic sensors, have already allowed, and they will do it more perfectly in the future, to build high perfection androids or cyborgs. They will collaborate with man and open new moral reflections to respect the ontological dignity in the new humanoid machines. In addition, both men and new androids will be in connection with huge external computer networks that will grow up to almost incredible levels the efficiency in the domain of body and nature. However, our current scientific knowledge, on the one hand, about hardware and software that will support both the humanoid machines and external computer networks, made with existing engineering (and also the foreseeable medium and even long term engineering and, on the other hand, our scientific knowledge about animal and human behavior from neural-biological structures that produce a psychic system, allow us to establish that there is no scientific basis to talk about an ontological identity between the computational machines and man. Accordingly, different ontologies (computational machines and biological entities will produce various different functional systems. There may be simulation, but never ontological identity. These ideas are essential to assess the transhumanism of Ray Kurzweil.

Computer control of shielded cell operations

International Nuclear Information System (INIS)

Jeffords, W.R. III.

1987-01-01

This paper describes in detail a computer system to remotely control shielded cell operations. System hardware, software, and design criteria are discussed. We have designed a computer-controlled buret that provides a tenfold improvement over the buret currently in service. A computer also automatically controls cell analyses, calibrations, and maintenance. This system improves conditions for the operators by providing a safer, more efficient working environment and is expandable for future growth and development

The changing world of modern cell biology.

Science.gov (United States)

Misteli, Tom

2009-01-12

Change is always ambiguous. There is the enticing prospect of novelty and better times ahead, but at the same time the concern of losing the good of the past. It is with these sentiments that I take over as the Editor-in-Chief from Ira Mellman who for a decade has cleverly and effectively lead the JCB. During this time he directed and oversaw an extensive modernization of the journal and guided it through dramatic changes in the publishing world. Ira lead the journal with unyielding dedication and enthusiasm and we in the cell biology community must thank him profoundly for his service. It is his work, together with the invaluable contribution of the best editorial board and the most dedicated professional editorial staff in the scientific publishing business, that allows me to now take over the stewardship of the JCB with a tremendous sense of excitement and determination to continue and expand the JCB's role as the leading journal in the cell biology community and as a trendsetter in the rapidly changing world of modern cell biology.

A framework to establish credibility of computational models in biology.

Science.gov (United States)

Patterson, Eann A; Whelan, Maurice P

2017-10-01

Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Investigating the role of retinal Müller cells with approaches in genetics and cell biology.

Science.gov (United States)

Fu, Suhua; Zhu, Meili; Ash, John D; Wang, Yunchang; Le, Yun-Zheng

2014-01-01

Müller cells are major macroglia and play many essential roles as a supporting cell in the retina. As Müller cells only constitute a small portion of retinal cells, investigating the role of Müller glia in retinal biology and diseases is particularly challenging. To overcome this problem, we first generated a Cre/lox-based conditional gene targeting system that permits the genetic manipulation and functional dissection of gene of interests in Müller cells. To investigate diabetes-induced alteration of Müller cells, we recently adopted methods to analyze Müller cells survival/death in vitro and in vivo. We also used normal and genetically altered primary cell cultures to reveal the mechanistic insights for Müller cells in biological and disease processes. In this article, we will discuss the applications and limitations of these methodologies, which may be useful for research in retinal Müller cell biology and pathophysiology.

Exploiting graphics processing units for computational biology and bioinformatics.

Science.gov (United States)

Payne, Joshua L; Sinnott-Armstrong, Nicholas A; Moore, Jason H

2010-09-01

Advances in the video gaming industry have led to the production of low-cost, high-performance graphics processing units (GPUs) that possess more memory bandwidth and computational capability than central processing units (CPUs), the standard workhorses of scientific computing. With the recent release of generalpurpose GPUs and NVIDIA's GPU programming language, CUDA, graphics engines are being adopted widely in scientific computing applications, particularly in the fields of computational biology and bioinformatics. The goal of this article is to concisely present an introduction to GPU hardware and programming, aimed at the computational biologist or bioinformaticist. To this end, we discuss the primary differences between GPU and CPU architecture, introduce the basics of the CUDA programming language, and discuss important CUDA programming practices, such as the proper use of coalesced reads, data types, and memory hierarchies. We highlight each of these topics in the context of computing the all-pairs distance between instances in a dataset, a common procedure in numerous disciplines of scientific computing. We conclude with a runtime analysis of the GPU and CPU implementations of the all-pairs distance calculation. We show our final GPU implementation to outperform the CPU implementation by a factor of 1700.

Evolutionary cell biology: functional insight from "endless forms most beautiful".

Science.gov (United States)

Richardson, Elisabeth; Zerr, Kelly; Tsaousis, Anastasios; Dorrell, Richard G; Dacks, Joel B

2015-12-15

In animal and fungal model organisms, the complexities of cell biology have been analyzed in exquisite detail and much is known about how these organisms function at the cellular level. However, the model organisms cell biologists generally use include only a tiny fraction of the true diversity of eukaryotic cellular forms. The divergent cellular processes observed in these more distant lineages are still largely unknown in the general scientific community. Despite the relative obscurity of these organisms, comparative studies of them across eukaryotic diversity have had profound implications for our understanding of fundamental cell biology in all species and have revealed the evolution and origins of previously observed cellular processes. In this Perspective, we will discuss the complexity of cell biology found across the eukaryotic tree, and three specific examples of where studies of divergent cell biology have altered our understanding of key functional aspects of mitochondria, plastids, and membrane trafficking. © 2015 Richardson et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Eduard Strasburger (1844-1912): founder of modern plant cell biology.

Science.gov (United States)

Volkmann, Dieter; Baluška, František; Menzel, Diedrik

2012-10-01

Eduard Strasburger, director of the Botany Institute and the Botanical Garden at the University of Bonn from 1881 to 1912, was one of the most admirable scientists in the field of plant biology, not just as the founder of modern plant cell biology but in addition as an excellent teacher who strongly believed in "education through science." He contributed to plant cell biology by discovering the discrete stages of karyokinesis and cytokinesis in algae and higher plants, describing cytoplasmic streaming in different systems, and reporting on the growth of the pollen tube into the embryo sac and guidance of the tube by synergides. Strasburger raised many problems which are hot spots in recent plant cell biology, e.g., structure and function of the plasmodesmata in relation to phloem loading (Strasburger cells) and signaling, mechanisms of cell plate formation, vesicle trafficking as a basis for most important developmental processes, and signaling related to fertilization.

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

Science.gov (United States)

Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antczak, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J; Guindani, Michele; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

2016-04-01

The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

Directory of Open Access Journals (Sweden)

Victor Trevino

2016-04-01

Full Text Available The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell

Scalable Computational Methods for the Analysis of High-Throughput Biological Data

Energy Technology Data Exchange (ETDEWEB)

Langston, Michael A. [Univ. of Tennessee, Knoxville, TN (United States)

2012-09-06

This primary focus of this research project is elucidating genetic regulatory mechanisms that control an organism's responses to low-dose ionizing radiation. Although low doses (at most ten centigrays) are not lethal to humans, they elicit a highly complex physiological response, with the ultimate outcome in terms of risk to human health unknown. The tools of molecular biology and computational science will be harnessed to study coordinated changes in gene expression that orchestrate the mechanisms a cell uses to manage the radiation stimulus. High performance implementations of novel algorithms that exploit the principles of fixed-parameter tractability will be used to extract gene sets suggestive of co-regulation. Genomic mining will be performed to scrutinize, winnow and highlight the most promising gene sets for more detailed investigation. The overall goal is to increase our understanding of the health risks associated with exposures to low levels of radiation.

Computational Systems Chemical Biology

OpenAIRE

Oprea, Tudor I.; May, Elebeoba E.; Leitão, Andrei; Tropsha, Alexander

2011-01-01

There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically-based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology, SCB (Oprea et al., 2007).

Systems biology perspectives on minimal and simpler cells.

Science.gov (United States)

Xavier, Joana C; Patil, Kiran Raosaheb; Rocha, Isabel

2014-09-01

The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Systems Biology Perspectives on Minimal and Simpler Cells

Science.gov (United States)

Xavier, Joana C.; Patil, Kiran Raosaheb

2014-01-01

SUMMARY The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells. PMID:25184563

Multiobjective optimization in bioinformatics and computational biology.

Science.gov (United States)

Handl, Julia; Kell, Douglas B; Knowles, Joshua

2007-01-01

This paper reviews the application of multiobjective optimization in the fields of bioinformatics and computational biology. A survey of existing work, organized by application area, forms the main body of the review, following an introduction to the key concepts in multiobjective optimization. An original contribution of the review is the identification of five distinct "contexts," giving rise to multiple objectives: These are used to explain the reasons behind the use of multiobjective optimization in each application area and also to point the way to potential future uses of the technique.

Impact of implementation choices on quantitative predictions of cell-based computational models

Science.gov (United States)

Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

2017-09-01

'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

Computational biology approaches to plant metabolism and photosynthesis: applications for corals in times of climate change and environmental stress.

Science.gov (United States)

Crabbe, M James C

2010-08-01

Knowledge of factors that are important in reef resilience helps us to understand how reef ecosystems react following major anthropogenic and environmental disturbances. The symbiotic relationship between the photosynthetic zooxanthellae algal cells and corals is that the zooxanthellae provide the coral with carbon, while the coral provides protection and access to enough light for the zooxanthellae to photosynthesise. This article reviews some recent advances in computational biology relevant to photosynthetic organisms, including Beyesian approaches to kinetics, computational methods for flux balances in metabolic processes, and determination of clades of zooxanthallae. Application of these systems will be important in the conservation of coral reefs in times of climate change and environmental stress.

Probing the biology of cell boundary conditions through confinement of Xenopus cell-free cytoplasmic extracts.

Science.gov (United States)

Bermudez, Jessica G; Chen, Hui; Einstein, Lily C; Good, Matthew C

2017-01-01

Cell-free cytoplasmic extracts prepared from Xenopus eggs and embryos have for decades provided a biochemical system with which to interrogate complex cell biological processes in vitro. Recently, the application of microfabrication and microfluidic strategies in biology has narrowed the gap between in vitro and in vivo studies by enabling formation of cell-size compartments containing functional cytoplasm. These approaches provide numerous advantages over traditional biochemical experiments performed in a test tube. Most notably, the cell-free cytoplasm is confined using a two- or three-dimensional boundary, which mimics the natural configuration of a cell. This strategy enables characterization of the spatial organization of a cell, and the role that boundaries play in regulating intracellular assembly and function. In this review, we describe the marriage of Xenopus cell-free cytoplasm and confinement technologies to generate synthetic cell-like systems, the recent biological insights they have enabled, and the promise they hold for future scientific discovery. © 2017 Wiley Periodicals, Inc.

CellNet: Network Biology Applied to Stem Cell Engineering

Science.gov (United States)

Cahan, Patrick; Li, Hu; Morris, Samantha A.; da Rocha, Edroaldo Lummertz; Daley, George Q.; Collins, James J.

2014-01-01

SUMMARY Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population, and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. PMID:25126793

CellNet: network biology applied to stem cell engineering.

Science.gov (United States)

Cahan, Patrick; Li, Hu; Morris, Samantha A; Lummertz da Rocha, Edroaldo; Daley, George Q; Collins, James J

2014-08-14

Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

A muscle stem cell for every muscle: variability of satellite cell biology among different muscle groups

Science.gov (United States)

Randolph, Matthew E.; Pavlath, Grace K.

2015-01-01

The human body contains approximately 640 individual skeletal muscles. Despite the fact that all of these muscles are composed of striated muscle tissue, the biology of these muscles and their associated muscle stem cell populations are quite diverse. Skeletal muscles are affected differentially by various muscular dystrophies (MDs), such that certain genetic mutations specifically alter muscle function in only a subset of muscles. Additionally, defective muscle stem cells have been implicated in the pathology of some MDs. The biology of muscle stem cells varies depending on the muscles with which they are associated. Here we review the biology of skeletal muscle stem cell populations of eight different muscle groups. Understanding the biological variation of skeletal muscles and their resident stem cells could provide valuable insight into mechanisms underlying the susceptibility of certain muscles to myopathic disease. PMID:26500547

The Emerging Cell Biology of Thyroid Stem Cells

Science.gov (United States)

Latif, Rauf; Minsky, Noga C.; Ma, Risheng

2011-01-01

Context: Stem cells are undifferentiated cells with the property of self-renewal and give rise to highly specialized cells under appropriate local conditions. The use of stem cells in regenerative medicine holds great promise for the treatment of many diseases, including those of the thyroid gland. Evidence Acquisition: This review focuses on the progress that has been made in thyroid stem cell research including an overview of cellular and molecular events (most of which were drawn from the period 1990–2011) and discusses the remaining problems encountered in their differentiation. Evidence Synthesis: Protocols for the in vitro differentiation of embryonic stem cells, based on normal developmental processes, have generated thyroid-like cells but without full thyrocyte function. However, agents have been identified, including activin A, insulin, and IGF-I, which are able to stimulate the generation of thyroid-like cells in vitro. In addition, thyroid stem/progenitor cells have been identified within the normal thyroid gland and within thyroid cancers. Conclusions: Advances in thyroid stem cell biology are providing not only insight into thyroid development but may offer therapeutic potential in thyroid cancer and future thyroid cell replacement therapy. PMID:21778219

Searching the literature for proteins facilitates the identification of biological processes, if advanced methods of analysis are linked: a case study on microgravity-caused changes in cells.

Science.gov (United States)

Bauer, Johann; Bussen, Markus; Wise, Petra; Wehland, Markus; Schneider, Sabine; Grimm, Daniela

2016-07-01

More than one hundred reports were published about the characterization of cells from malignant and healthy tissues, as well as of endothelial cells and stem cells exposed to microgravity conditions. We retrieved publications about microgravity related studies on each type of cells, extracted the proteins mentioned therein and analyzed them aiming to identify biological processes affected by microgravity culture conditions. The analysis revealed 66 different biological processes, 19 of them were always detected when papers about the four types of cells were analyzed. Since a response to the removal of gravity is common to the different cell types, some of the 19 biological processes could play a role in cellular adaption to microgravity. Applying computer programs, to extract and analyze proteins and genes mentioned in publications becomes essential for scientists interested to get an overview of the rapidly growing fields of gravitational biology and space medicine.

Scientific Computing Kernels on the Cell Processor

Energy Technology Data Exchange (ETDEWEB)

Williams, Samuel W.; Shalf, John; Oliker, Leonid; Kamil, Shoaib; Husbands, Parry; Yelick, Katherine

2007-04-04

The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of using the recently-released STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key scientific computing kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. The difficulty of programming Cell, which requires assembly level intrinsics for the best performance, makes this model useful as an initial step in algorithm design and evaluation. Next, we validate the accuracy of our model by comparing results against published hardware results, as well as our own implementations on a 3.2GHz Cell blade. Additionally, we compare Cell performance to benchmarks run on leading superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1E) architectures. Our work also explores several different mappings of the kernels and demonstrates a simple and effective programming model for Cell's unique architecture. Finally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

Science.gov (United States)

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.

S100A4 and its role in metastasis – computational integration of data on biological networks.

Science.gov (United States)

Buetti-Dinh, Antoine; Pivkin, Igor V; Friedman, Ran

2015-08-01

Characterising signal transduction networks is fundamental to our understanding of biology. However, redundancy and different types of feedback mechanisms make it difficult to understand how variations of the network components contribute to a biological process. In silico modelling of signalling interactions therefore becomes increasingly useful for the development of successful therapeutic approaches. Unfortunately, quantitative information cannot be obtained for all of the proteins or complexes that comprise the network, which limits the usability of computational models. We developed a flexible computational framework for the analysis of biological signalling networks. We demonstrate our approach by studying the mechanism of metastasis promotion by the S100A4 protein, and suggest therapeutic strategies. The advantage of the proposed method is that only limited information (interaction type between species) is required to set up a steady-state network model. This permits a straightforward integration of experimental information where the lack of details are compensated by efficient sampling of the parameter space. We investigated regulatory properties of the S100A4 network and the role of different key components. The results show that S100A4 enhances the activity of matrix metalloproteinases (MMPs), causing higher cell dissociation. Moreover, it leads to an increased stability of the pathological state. Thus, avoiding metastasis in S100A4-expressing tumours requires multiple target inhibition. Moreover, the analysis could explain the previous failure of MMP inhibitors in clinical trials. Finally, our method is applicable to a wide range of biological questions that can be represented as directional networks.

Systems-biology dissection of eukaryotic cell growth

Directory of Open Access Journals (Sweden)

Andrews Justen

2010-05-01

Full Text Available Abstract A recent article in BMC Biology illustrates the use of a systems-biology approach to integrate data across the transcriptome, proteome and metabolome of budding yeast in order to dissect the relationship between nutrient conditions and cell growth. See research article http://jbiol.com/content/6/2/4 and http://www.biomedcentral.com/1741-7007/8/68

Illuminating Cell Biology

Science.gov (United States)

2002-01-01

NASA's Ames Research Center awarded Ciencia, Inc., a Small Business Innovation Research contract to develop the Cell Fluorescence Analysis System (CFAS) to address the size, mass, and power constraints of using fluorescence spectroscopy in the International Space Station's Life Science Research Facility. The system will play an important role in studying biological specimen's long-term adaptation to microgravity. Commercial applications for the technology include diverse markets such as food safety, in situ environmental monitoring, online process analysis, genomics and DNA chips, and non-invasive diagnostics. Ciencia has already sold the system to the private sector for biosensor applications.

Controllability and observability of Boolean networks arising from biology

Science.gov (United States)

Li, Rui; Yang, Meng; Chu, Tianguang

2015-02-01

Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.

ADAM: analysis of discrete models of biological systems using computer algebra.

Science.gov (United States)

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web

Secure Encapsulation and Publication of Biological Services in the Cloud Computing Environment

Science.gov (United States)

Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

2013-01-01

Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved. PMID:24078906

Secure Encapsulation and Publication of Biological Services in the Cloud Computing Environment

Directory of Open Access Journals (Sweden)

Weizhe Zhang

2013-01-01

Full Text Available Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved.

Secure encapsulation and publication of biological services in the cloud computing environment.

Science.gov (United States)

Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

2013-01-01

Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved.

Parallel computing and molecular dynamics of biological membranes

International Nuclear Information System (INIS)

La Penna, G.; Letardi, S.; Minicozzi, V.; Morante, S.; Rossi, G.C.; Salina, G.

1998-01-01

In this talk I discuss the general question of the portability of molecular dynamics codes for diffusive systems on parallel computers of the APE family. The intrinsic single precision of the today available platforms does not seem to affect the numerical accuracy of the simulations, while the absence of integer addressing from CPU to individual nodes puts strong constraints on possible programming strategies. Liquids can be satisfactorily simulated using the ''systolic'' method. For more complex systems, like the biological ones at which we are ultimately interested in, the ''domain decomposition'' approach is best suited to beat the quadratic growth of the inter-molecular computational time with the number of atoms of the system. The promising perspectives of using this strategy for extensive simulations of lipid bilayers are briefly reviewed. (orig.)

Influence of cell printing on biological characters of chondrocytes.

Science.gov (United States)

Qu, Miao; Gao, Xiaoyan; Hou, Yikang; Shen, Congcong; Xu, Yourong; Zhu, Ming; Wang, Hengjian; Xu, Haisong; Chai, Gang; Zhang, Yan

2015-01-01

To establish a two-dimensional biological printing technique of chondrocytes and compare the difference of related biological characters between printed chondrocytes and unprinted cells so as to control the cell transfer process and keep cell viability after printing. Primary chondrocytes were obtained from human mature and fetal cartilage tissues and then were regularly sub-cultured to harvest cells at passage 2 (P2), which were adjusted to the single cell suspension at a density of 1×10(6)/mL. The experiment was divided into 2 groups: experimental group P2 chondrocytes were transferred by rapid prototype biological printer (driving voltage value 50 V, interval in x-axis 300 μm, interval in y-axis 1500 μm). Afterwards Live/Dead viability Kit and flow cytometry were respectively adopted to detect cell viability; CCK-8 Kit was adopted to detect cell proliferation viability; immunocytochemistry, immunofluorescence and RT-PCR was employed to identify related markers of chondrocytes; control group steps were the same as the printing group except that cell suspension received no printing. Fluorescence microscopy and flow cytometry analyses showed that there was no significant difference between experimental group and control group in terms of cell viability. After 7-day in vitro culture, control group exhibited higher O.D values than experimental group from 2nd day to 7th day but there was no distinct difference between these two groups (P>0.05). Inverted microscope observation demonstrated that the morphology of these two groups had no significant difference either. Similarly, Immunocytochemistry, immunofluorescence and RT-PCR assays also showed that there was no significant difference in the protein and gene expression of type II collagen and aggrecan between these two groups (P>0.05). Conclusion Cell printing has no distinctly negative effect on cell vitality, proliferation and phenotype of chondrocytes. Biological printing technique may provide a novel approach

Micro-separation toward systems biology.

Science.gov (United States)

Liu, Bi-Feng; Xu, Bo; Zhang, Guisen; Du, Wei; Luo, Qingming

2006-02-17

Current biology is experiencing transformation in logic or philosophy that forces us to reevaluate the concept of cell, tissue or entire organism as a collection of individual components. Systems biology that aims at understanding biological system at the systems level is an emerging research area, which involves interdisciplinary collaborations of life sciences, computational and mathematical sciences, systems engineering, and analytical technology, etc. For analytical chemistry, developing innovative methods to meet the requirement of systems biology represents new challenges as also opportunities and responsibility. In this review, systems biology-oriented micro-separation technologies are introduced for comprehensive profiling of genome, proteome and metabolome, characterization of biomolecules interaction and single cell analysis such as capillary electrophoresis, ultra-thin layer gel electrophoresis, micro-column liquid chromatography, and their multidimensional combinations, parallel integrations, microfabricated formats, and nano technology involvement. Future challenges and directions are also suggested.

Tiny cells meet big questions: a closer look at bacterial cell biology.

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Goley, Erin D

2013-04-01

While studying actin assembly as a graduate student with Matt Welch at the University of California at Berkeley, my interest was piqued by reports of surprising observations in bacteria: the identification of numerous cytoskeletal proteins, actin homologues fulfilling spindle-like functions, and even the presence of membrane-bound organelles. Curiosity about these phenomena drew me to Lucy Shapiro's lab at Stanford University for my postdoctoral research. In the Shapiro lab, and now in my lab at Johns Hopkins, I have focused on investigating the mechanisms of bacterial cytokinesis. Spending time as both a eukaryotic cell biologist and a bacterial cell biologist has convinced me that bacterial cells present the same questions as eukaryotic cells: How are chromosomes organized and accurately segregated? How is force generated for cytokinesis? How is polarity established? How are signals transduced within and between cells? These problems are conceptually similar between eukaryotes and bacteria, although their solutions can differ significantly in specifics. In this Perspective, I provide a broad view of cell biological phenomena in bacteria, the technical challenges facing those of us who peer into bacterial cells, and areas of common ground as research in eukaryotic and bacterial cell biology moves forward.

Knowledge Gaps in Rodent Pancreas Biology: Taking Human Pluripotent Stem Cell-Derived Pancreatic Beta Cells into Our Own Hands.

Science.gov (United States)

Santosa, Munirah Mohamad; Low, Blaise Su Jun; Pek, Nicole Min Qian; Teo, Adrian Kee Keong

2015-01-01

In the field of stem cell biology and diabetes, we and others seek to derive mature and functional human pancreatic β cells for disease modeling and cell replacement therapy. Traditionally, knowledge gathered from rodents is extended to human pancreas developmental biology research involving human pluripotent stem cells (hPSCs). While much has been learnt from rodent pancreas biology in the early steps toward Pdx1(+) pancreatic progenitors, much less is known about the transition toward Ngn3(+) pancreatic endocrine progenitors. Essentially, the later steps of pancreatic β cell development and maturation remain elusive to date. As a result, the most recent advances in the stem cell and diabetes field have relied upon combinatorial testing of numerous growth factors and chemical compounds in an arbitrary trial-and-error fashion to derive mature and functional human pancreatic β cells from hPSCs. Although this hit-or-miss approach appears to have made some headway in maturing human pancreatic β cells in vitro, its underlying biology is vaguely understood. Therefore, in this mini-review, we discuss some of these late-stage signaling pathways that are involved in human pancreatic β cell differentiation and highlight our current understanding of their relevance in rodent pancreas biology. Our efforts here unravel several novel signaling pathways that can be further studied to shed light on unexplored aspects of rodent pancreas biology. New investigations into these signaling pathways are expected to advance our knowledge in human pancreas developmental biology and to aid in the translation of stem cell biology in the context of diabetes treatments.

Biology and flow cytometry of proangiogenic hematopoietic progenitors cells.

Science.gov (United States)

Rose, Jonathan A; Erzurum, Serpil; Asosingh, Kewal

2015-01-01

During development, hematopoiesis and neovascularization are closely linked to each other via a common bipotent stem cell called the hemangioblast that gives rise to both hematopoietic cells and endothelial cells. In postnatal life, this functional connection between the vasculature and hematopoiesis is maintained by a subset of hematopoietic progenitor cells endowed with the capacity to differentiate into potent proangiogenic cells. These proangiogenic hematopoietic progenitors comprise a specific subset of bone marrow (BM)-derived cells that homes to sites of neovascularization and possess potent paracrine angiogenic activity. There is emerging evidence that this subpopulation of hematopoietic progenitors plays a critical role in vascular health and disease. Their angiogenic activity is distinct from putative "endothelial progenitor cells" that become structural cells of the endothelium by differentiation into endothelial cells. Proangiogenic hematopoietic progenitor cell research requires multidisciplinary expertise in flow cytometry, hematology, and vascular biology. This review provides a comprehensive overview of proangiogenic hematopoietic progenitor cell biology and flow cytometric methods to detect these cells in the peripheral blood circulation and BM. © 2014 International Society for Advancement of Cytometry.

On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

KAUST Repository

Moreo, P.

2009-11-14

The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise to higher level structure. Given cells respond to mechanical stimuli, it is therefore important to consider the effects of these responses within biological self-organisation models. Here, we consider the self-organisation properties of a mechanochemical model previously developed by three of the authors in Acta Biomater. 4, 613-621 (2008), which is capable of reproducing the behaviour of a population of cells cultured on an elastic substrate in response to a variety of stimuli. In particular, we examine the conditions under which stable spatial patterns can emerge with this model, focusing on the influence of mechanical stimuli and the interplay of non-local phenomena. To this end, we have performed a linear stability analysis and numerical simulations based on a mixed finite element formulation, which have allowed us to study the dynamical behaviour of the system in terms of the qualitative shape of the dispersion relation. We show that the consideration of mechanotaxis, namely changes in migration speeds and directions in response to mechanical stimuli alters the conditions for pattern formation in a singular manner. Furthermore without non-local effects, responses to mechanical stimuli are observed to result in dispersion relations with positive growth rates at arbitrarily large wavenumbers, in turn yielding heterogeneity at the cellular level in model predictions. This highlights the sensitivity and necessity of non-local effects in mechanically influenced biological pattern formation models and the ultimate failure of the continuum approximation in their absence. © 2009 Society for Mathematical Biology.

Cell adhesive ability of a biological foam ceramic with surface modification

International Nuclear Information System (INIS)

Zhang Yong; Li Xiaoyu; Feng Fan; Lin Yunfeng; Liao Yunmao; Tian, Weidong; Liu Lei

2008-01-01

Biological foam ceramic is a promising material for tissue engineering scaffold because of its biocompatibility, biodegradation and adequate pores measured from micrometer to nanometers. The aim of this study was to evaluate the adhesion and proliferation of adipose-derived stromal cells (ADSCs) on the biological foam ceramic coated with fibronectin. ADSCs were harvested from SD rats and passaged three times prior to seeding onto biological foam surface modified with fibronectin (50 μg/ml). Scaffold without surface modification served as control. To characterize cellular attachment, cells were incubated on the scaffold for 1 h and 3 h and then the cells attached onto the scaffold were counted. The difference of proliferation was appraised using MTT assay at day 1, 3, 5 and 7 before the cells reached confluence. After 7 days of culture, scanning electron microscope (SEM) was chosen to assess cell morphology and attachment of ADSCs on the biological foam ceramic. Attachment of ADSCs on the biological foam ceramic surface modified with fibronectin at 1 h or 3 h was substantially greater than that in control. MTT assay revealed that ADSCs proliferation tendency of the experimental group was nearly parallel to that of control. SEM view showed that ADSCs in the experimental groups connected more tightly and excreted more collagen than that in control. The coating of fibronectin could improve the cell adhesive ability of biological foam ceramics without evident effect on proliferation

Compact Electro-Permeabilization System for Controlled Treatment of Biological Cells and Cell Medium Conductivity Change Measurement

Directory of Open Access Journals (Sweden)

Novickij Vitalij

2014-10-01

Full Text Available Subjection of biological cells to high intensity pulsed electric field results in the permeabilization of the cell membrane. Measurement of the electrical conductivity change allows an analysis of the dynamics of the process, determination of the permeabilization thresholds, and ion efflux influence. In this work a compact electro-permeabilization system for controlled treatment of biological cells is presented. The system is capable of delivering 5 μs - 5 ms repetitive square wave electric field pulses with amplitude up to 1 kV. Evaluation of the cell medium conductivity change is implemented in the setup, allowing indirect measurement of the ion concentration changes occurring due to the cell membrane permeabilization. The simulation model using SPICE and the experimental data of the proposed system are presented in this work. Experimental data with biological cells is also overviewed

Virtual Reconstruction and Three-Dimensional Printing of Blood Cells as a Tool in Cell Biology Education.

Science.gov (United States)

Augusto, Ingrid; Monteiro, Douglas; Girard-Dias, Wendell; Dos Santos, Thaisa Oliveira; Rosa Belmonte, Simone Letícia; Pinto de Oliveira, Jairo; Mauad, Helder; da Silva Pacheco, Marcos; Lenz, Dominik; Stefanon Bittencourt, Athelson; Valentim Nogueira, Breno; Lopes Dos Santos, Jorge Roberto; Miranda, Kildare; Guimarães, Marco Cesar Cunegundes

2016-01-01

The cell biology discipline constitutes a highly dynamic field whose concepts take a long time to be incorporated into the educational system, especially in developing countries. Amongst the main obstacles to the introduction of new cell biology concepts to students is their general lack of identification with most teaching methods. The introduction of elaborated figures, movies and animations to textbooks has given a tremendous contribution to the learning process and the search for novel teaching methods has been a central goal in cell biology education. Some specialized tools, however, are usually only available in advanced research centers or in institutions that are traditionally involved with the development of novel teaching/learning processes, and are far from becoming reality in the majority of life sciences schools. When combined with the known declining interest in science among young people, a critical scenario may result. This is especially important in the field of electron microscopy and associated techniques, methods that have greatly contributed to the current knowledge on the structure and function of different cell biology models but are rarely made accessible to most students. In this work, we propose a strategy to increase the engagement of students into the world of cell and structural biology by combining 3D electron microscopy techniques and 3D prototyping technology (3D printing) to generate 3D physical models that accurately and realistically reproduce a close-to-the native structure of the cell and serve as a tool for students and teachers outside the main centers. We introduce three strategies for 3D imaging, modeling and prototyping of cells and propose the establishment of a virtual platform where different digital models can be deposited by EM groups and subsequently downloaded and printed in different schools, universities, research centers and museums, thereby modernizing teaching of cell biology and increasing the accessibility to

Introducing the RadBioStat Educational Software: Computer-Assisted Teaching of the Random Nature of Cell Killing

Directory of Open Access Journals (Sweden)

Safari A

2014-06-01

Full Text Available The interaction of radiation with cells and tissues has a random nature. Therefore, understanding the random nature of cell killing that is determined by Poisson distribution statistics is an essential point in education of radiation biology. RadBioStat is a newly developed educational MATLAB-based software designed for computer-assisted learning of the target theory in radiation biology. Although its potential applications is developing rapidly, currently RadBioStat software can be a useful tool in computerassisted education of radiobiological models such as single target single hit, multiple target single hit and multiple target multiple hit. Scholars’ feedback is valuable to the producers of this software and help them continuously improve this product, add new features and increase its desirability and functionality.

Muscle Satellite Cells: Exploring the Basic Biology to Rule Them.

Science.gov (United States)

Almeida, Camila F; Fernandes, Stephanie A; Ribeiro Junior, Antonio F; Keith Okamoto, Oswaldo; Vainzof, Mariz

2016-01-01

Adult skeletal muscle is a postmitotic tissue with an enormous capacity to regenerate upon injury. This is accomplished by resident stem cells, named satellite cells, which were identified more than 50 years ago. Since their discovery, many researchers have been concentrating efforts to answer questions about their origin and role in muscle development, the way they contribute to muscle regeneration, and their potential to cell-based therapies. Satellite cells are maintained in a quiescent state and upon requirement are activated, proliferating, and fusing with other cells to form or repair myofibers. In addition, they are able to self-renew and replenish the stem pool. Every phase of satellite cell activity is highly regulated and orchestrated by many molecules and signaling pathways; the elucidation of players and mechanisms involved in satellite cell biology is of extreme importance, being the first step to expose the crucial points that could be modulated to extract the optimal response from these cells in therapeutic strategies. Here, we review the basic aspects about satellite cells biology and briefly discuss recent findings about therapeutic attempts, trying to raise questions about how basic biology could provide a solid scaffold to more successful use of these cells in clinics.

Plasma cell leukemia: update on biology and therapy.

Science.gov (United States)

Mina, Roberto; D'Agostino, Mattia; Cerrato, Chiara; Gay, Francesca; Palumbo, Antonio

2017-07-01

Plasma cell leukemia (PCL) is a rare, but very aggressive, plasma cell dyscrasia, representing a distinct clinicopathological entity as compared to multiple myeloma (MM), with peculiar biological and clinical features. A hundred times rarer than MM, the disease course is characterized by short remissions and poor survival. PCL is defined by an increased percentage (>20%) and absolute number (>2 × 10 9 /l) of plasma cells in the peripheral blood. PCL is defined as 'primary' when peripheral plasmacytosis is detected at diagnosis, 'secondary' when leukemization occurs in a patient with preexisting MM. Novel agents have revolutionized the outcomes of MM patients and have been introduced also for the treatment of PCL. Here, we provide an update on biology and treatment options for PCL.

Integrating biological redesign: where synthetic biology came from and where it needs to go.

Science.gov (United States)

Way, Jeffrey C; Collins, James J; Keasling, Jay D; Silver, Pamela A

2014-03-27

Synthetic biology seeks to extend approaches from engineering and computation to redesign of biology, with goals such as generating new chemicals, improving human health, and addressing environmental issues. Early on, several guiding principles of synthetic biology were articulated, including design according to specification, separation of design from fabrication, use of standardized biological parts and organisms, and abstraction. We review the utility of these principles over the past decade in light of the field's accomplishments in building complex systems based on microbial transcription and metabolism and describe the progress in mammalian cell engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

Multispectral optical tweezers for molecular diagnostics of single biological cells

Science.gov (United States)

Butler, Corey; Fardad, Shima; Sincore, Alex; Vangheluwe, Marie; Baudelet, Matthieu; Richardson, Martin

2012-03-01

Optical trapping of single biological cells has become an established technique for controlling and studying fundamental behavior of single cells with their environment without having "many-body" interference. The development of such an instrument for optical diagnostics (including Raman and fluorescence for molecular diagnostics) via laser spectroscopy with either the "trapping" beam or secondary beams is still in progress. This paper shows the development of modular multi-spectral imaging optical tweezers combining Raman and Fluorescence diagnostics of biological cells.

"Known Unknowns": Current Questions in Muscle Satellite Cell Biology.

Science.gov (United States)

Cornelison, Ddw

2018-01-01

Our understanding of satellite cells, now known to be the obligate stem cells of skeletal muscle, has increased dramatically in recent years due to the introduction of new molecular, genetic, and technical resources. In addition to their role in acute repair of damaged muscle, satellite cells are of interest in the fields of aging, exercise, neuromuscular disease, and stem cell therapy, and all of these applications have driven a dramatic increase in our understanding of the activity and potential of satellite cells. However, many fundamental questions of satellite cell biology remain to be answered, including their emergence as a specific lineage, the degree and significance of heterogeneity within the satellite cell population, the roles of their interactions with other resident and infiltrating cell types during homeostasis and regeneration, and the relative roles of intrinsic vs extrinsic factors that may contribute to satellite cell dysfunction in the context of aging or disease. This review will address the current state of these open questions in satellite cell biology. © 2018 Elsevier Inc. All rights reserved.

Mobile Applications in Cell Biology Present New Approaches for Cell Modelling

Science.gov (United States)

de Oliveira, Mayara Lustosa; Galembeck, Eduardo

2016-01-01

Cell biology apps were surveyed in order to identify whether there are new approaches for modelling cells allowed by the new technologies implemented in tablets and smartphones. A total of 97 apps were identified in 3 stores surveyed (Apple, Google Play and Amazon), they are presented as: education 48.4%, games 26.8% and medicine 15.4%. The apps…

Prototype Biology-Based Radiation Risk Module Project

Science.gov (United States)

Terrier, Douglas; Clayton, Ronald G.; Patel, Zarana; Hu, Shaowen; Huff, Janice

2015-01-01

Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

The species translation challenge-a systems biology perspective on human and rat bronchial epithelial cells.

Science.gov (United States)

Poussin, Carine; Mathis, Carole; Alexopoulos, Leonidas G; Messinis, Dimitris E; Dulize, Rémi H J; Belcastro, Vincenzo; Melas, Ioannis N; Sakellaropoulos, Theodore; Rhrissorrakrai, Kahn; Bilal, Erhan; Meyer, Pablo; Talikka, Marja; Boué, Stéphanie; Norel, Raquel; Rice, John J; Stolovitzky, Gustavo; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

2014-01-01

The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to 'translate' the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies.

The species translation challenge—A systems biology perspective on human and rat bronchial epithelial cells

Science.gov (United States)

Poussin, Carine; Mathis, Carole; Alexopoulos, Leonidas G; Messinis, Dimitris E; Dulize, Rémi H J; Belcastro, Vincenzo; Melas, Ioannis N; Sakellaropoulos, Theodore; Rhrissorrakrai, Kahn; Bilal, Erhan; Meyer, Pablo; Talikka, Marja; Boué, Stéphanie; Norel, Raquel; Rice, John J; Stolovitzky, Gustavo; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

2014-01-01

The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to ‘translate’ the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies. PMID:25977767

Nanobiotechnology meets plant cell biology: Carbon nanotubes as organelle targeting nanocarriers

KAUST Repository

Serag, Maged F.; Kaji, Noritada; Habuchi, Satoshi; Bianco, Alberto; Baba, Yoshinobu

2013-01-01

For years, nanotechnology has shown great promise in the fields of biomedical and biotechnological sciences and medical research. In this review, we demonstrate its versatility and applicability in plant cell biology studies. Specifically, we discuss the ability of functionalized carbon nanotubes to penetrate the plant cell wall, target specific organelles, probe protein-carrier activity and induce organelle recycling in plant cells. We also, shed light on prospective applications of carbon nanomaterials in cell biology and plant cell transformation. © 2013 The Royal Society of Chemistry.

Nanomaterials modulate stem cell differentiation: biological interaction and underlying mechanisms.

Science.gov (United States)

Wei, Min; Li, Song; Le, Weidong

2017-10-25

Stem cells are unspecialized cells that have the potential for self-renewal and differentiation into more specialized cell types. The chemical and physical properties of surrounding microenvironment contribute to the growth and differentiation of stem cells and consequently play crucial roles in the regulation of stem cells' fate. Nanomaterials hold great promise in biological and biomedical fields owing to their unique properties, such as controllable particle size, facile synthesis, large surface-to-volume ratio, tunable surface chemistry, and biocompatibility. Over the recent years, accumulating evidence has shown that nanomaterials can facilitate stem cell proliferation and differentiation, and great effort is undertaken to explore their possible modulating manners and mechanisms on stem cell differentiation. In present review, we summarize recent progress in the regulating potential of various nanomaterials on stem cell differentiation and discuss the possible cell uptake, biological interaction and underlying mechanisms.

The bottom-up approach to defining life : deciphering the functional organization of biological cells via multi-objective representation of biological complexity from molecules to cells

Directory of Open Access Journals (Sweden)

Sathish ePeriyasamy

2013-12-01

Full Text Available In silico representation of cellular systems needs to represent the adaptive dynamics of biological cells, recognizing a cell’s multi-objective topology formed by spatially and temporally cohesive intracellular structures. The design of these models needs to address the hierarchical and concurrent nature of cellular functions and incorporate the ability to self-organise in response to transitions between healthy and pathological phases, and adapt accordingly. The functions of biological systems are constantly evolving, due to the ever changing demands of their environment. Biological systems meet these demands by pursuing objectives, aided by their constituents, giving rise to biological functions. A biological cell is organised into an objective/task hierarchy. These objective hierarchy corresponds to the nested nature of temporally cohesive structures and representing them will facilitate in studying pleiotropy and polygeny by modeling causalities propagating across multiple interconnected intracellular processes. Although biological adaptations occur in physiological, developmental and reproductive timescales, the paper is focused on adaptations that occur within physiological timescales, where the biomolecular activities contributing to functional organisation, play a key role in cellular physiology. The paper proposes a multi-scale and multi-objective modelling approach from the bottom-up by representing temporally cohesive structures for multi-tasking of intracellular processes. Further the paper characterises the properties and constraints that are consequential to the organisational and adaptive dynamics in biological cells.

Computer modeling in developmental biology: growing today, essential tomorrow.

Science.gov (United States)

Sharpe, James

2017-12-01

D'Arcy Thompson was a true pioneer, applying mathematical concepts and analyses to the question of morphogenesis over 100 years ago. The centenary of his famous book, On Growth and Form , is therefore a great occasion on which to review the types of computer modeling now being pursued to understand the development of organs and organisms. Here, I present some of the latest modeling projects in the field, covering a wide range of developmental biology concepts, from molecular patterning to tissue morphogenesis. Rather than classifying them according to scientific question, or scale of problem, I focus instead on the different ways that modeling contributes to the scientific process and discuss the likely future of modeling in developmental biology. © 2017. Published by The Company of Biologists Ltd.

Cells from icons to symbols: molecularizing cell biology in the 1980s.

Science.gov (United States)

Serpente, Norberto

2011-12-01

Over centuries cells have been the target of optical and electronic microscopes as well as others technologies, with distinctive types of visual output. Whilst optical technologies produce images 'evident to the eye', the electronic and especially the molecular create images that are more elusive to conceptualization and assessment. My study applies the semiotic approach to the production of images in cell biology to capture the shift from microscopic images to non-traditional visual technologies around 1980. Here I argue that the visual shift that coincides with the growing dominance of molecular biology involves a change from iconic to symbolic forms. Copyright © 2011 Elsevier Ltd. All rights reserved.

The central dogma of cell biology.

Science.gov (United States)

Cooper, S

1981-06-01

The Continuum Model proposes that preparations for DNA synthesis occur continuously during all phases of the division cycle. Various stimuli activate cell proliferation by changing the rate of initiator (protein) synthesis. Cell division does not initiate any process regulating cell proliferation. Cell division is the end of a process and the beginning of nothing. The alternative model which has cell proliferation regulated in the G1 phase of the division cycle is reexamined and the two types of evidence for this model, G1-variability and G1-arrest are shown to be compatible with the Continuum Model. Here, the Continuum Model is generalized to produce a new look at the logic of the division cycle in prokaryotes and eukaryotes. This new view, the Central Dogma of Cell Biology, is presented and two predictions are made. I propose that (i) cell division does not have any regulatory function, and (ii) that DNA synthesis may, indeed, have some affect on the synthesis of initiator.

Discovery of HeLa Cell Contamination in HES Cells: Call for Cell Line Authentication in Reproductive Biology Research.

Science.gov (United States)

Kniss, Douglas A; Summerfield, Taryn L

2014-08-01

Continuous cell lines are used frequently in reproductive biology research to study problems in early pregnancy events and parturition. It has been recognized for 50 years that many mammalian cell lines contain inter- or intraspecies contaminations with other cells. However, most investigators do not routinely test their culture systems for cross-contamination. The most frequent contributor to cross-contamination of cell lines is the HeLa cell isolated from an aggressive cervical adenocarcinoma. We report on the discovery of HeLa cell contamination of the human endometrial epithelial cell line HES isolated in our laboratory. Short tandem repeat analysis of 9 unique genetic loci demonstrated molecular identity between HES and HeLa cells. In addition, we verified that WISH cells, isolated originally from human amnion epithelium, were also contaminated with HeLa cells. Inasmuch as our laboratory did not culture HeLa cells at the time of HES cell derivations, the source of contamination was the WISH cell line. These data highlight the need for continued diligence in authenticating cell lines used in reproductive biology research. © The Author(s) 2014.

Biophysical mechanisms complementing "classical" cell biology.

Science.gov (United States)

Funk, Richard H W

2018-01-01

This overview addresses phenomena in cell- and molecular biology which are puzzling by their fast and highly coordinated way of organization. Generally, it appears that informative processes probably involved are more on the biophysical than on the classical biochemical side. The coordination problem is explained within the first part of the review by the topic of endogenous electrical phenomena. These are found e.g. in fast tissue organization and reorganization processes like development, wound healing and regeneration. Here, coupling into classical biochemical signaling and reactions can be shown by modern microscopy, electronics and bioinformatics. Further, one can follow the triggered reactions seamlessly via molecular biology till into genetics. Direct observation of intracellular electric processes is very difficult because of e.g. shielding through the cell membrane and damping by other structures. Therefore, we have to rely on photonic and photon - phonon coupling phenomena like molecular vibrations, which are addressed within the second part. Molecules normally possess different charge moieties and thus small electromagnetic (EMF) patterns arise during molecular vibration. These patterns can now be measured best within the optical part of the spectrum - much less in the lower terahertz till kHz and lower Hz part (third part of this review). Finally, EMFs facilitate quantum informative processes in coherent domains of molecular, charge and electron spin motion. This helps to coordinate such manifold and intertwined processes going on within cells, tissues and organs (part 4). Because the phenomena described in part 3 and 4 of the review still await really hard proofs we need concerted efforts and a combination of biophysics, molecular biology and informatics to unravel the described mysteries in "physics of life".

Mathematical computer simulation of the process of ultrasound interaction with biological medium

International Nuclear Information System (INIS)

Yakovleva, T.; Nassiri, D.; Ciantar, D.

1996-01-01

The aim of the paper is to study theoretically the interaction of ultrasound irradiation with biological medium and the peculiarities of ultrasound scattering by inhomogeneities of biological tissue, which can be represented by fractal structures. This investigation has been used for the construction of the computer model of three-dimensional ultrasonic imaging system what gives the possibility to define more accurately the pathological changes in such a tissue by means of its image analysis. Poster 180. (author)

Getting the measure of things: the physical biology of stem cells.

Science.gov (United States)

Lowell, Sally

2013-10-01

In July 2013, the diverse fields of biology, physics and mathematics converged to discuss 'The Physical Biology of Stem Cells', the subject of the third annual symposium of the Cambridge Stem Cell Institute, UK. Two clear themes resonated throughout the meeting: the new insights gained from advances in the acquisition and interpretation of quantitative data; and the importance of 'thinking outside the nucleus' to consider physical influences on cell fate.

Tensegrity I. Cell structure and hierarchical systems biology

Science.gov (United States)

Ingber, Donald E.

2003-01-01

In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

Science.gov (United States)

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

Synthetic biology in mammalian cells: Next generation research tools and therapeutics

Science.gov (United States)

Lienert, Florian; Lohmueller, Jason J; Garg, Abhishek; Silver, Pamela A

2014-01-01

Recent progress in DNA manipulation and gene circuit engineering has greatly improved our ability to programme and probe mammalian cell behaviour. These advances have led to a new generation of synthetic biology research tools and potential therapeutic applications. Programmable DNA-binding domains and RNA regulators are leading to unprecedented control of gene expression and elucidation of gene function. Rebuilding complex biological circuits such as T cell receptor signalling in isolation from their natural context has deepened our understanding of network motifs and signalling pathways. Synthetic biology is also leading to innovative therapeutic interventions based on cell-based therapies, protein drugs, vaccines and gene therapies. PMID:24434884

Progenitor cells in the kidney: biology and therapeutic perspectives

NARCIS (Netherlands)

Rookmaaker, M.B.; Verhaar, M.C.; Zonneveld, A.J. van; Rabelink, T.J.

2004-01-01

Progenitor cells in the kidney: Biology and therapeutic perspectives. The stem cell may be viewed as an engineer who can read the blue print and become the building. The role of this fascinating cell in physiology and pathophysiology has recently attracted a great deal of interest. The archetype of

Alkali-treated titanium selectively regulating biological behaviors of bacteria, cancer cells and mesenchymal stem cells.

Science.gov (United States)

Li, Jinhua; Wang, Guifang; Wang, Donghui; Wu, Qianju; Jiang, Xinquan; Liu, Xuanyong

2014-12-15

Many attentions have been paid to the beneficial effect of alkali-treated titanium to bioactivity and osteogenic activity, but few to the other biological effect. In this work, hierarchical micro/nanopore films were prepared on titanium surface by acid etching and alkali treatment and their biological effects on bacteria, cancer cells and mesenchymal stem cells were investigated. Gram-positive Staphylococcus aureus, Gram-negative Escherichia coli, and human cholangiocarcinoma cell line RBE were used to investigate whether alkali-treated titanium can influence behaviors of bacteria and cancer cells. Responses of bone marrow mesenchymal stem cells (BMMSCs) to alkali-treated titanium were also subsequently investigated. The alkali-treated titanium can potently reduce bacterial adhesion, inhibit RBE and BMMSCs proliferation, while can better promote BMMSCs osteogenesis and angiogenesis than acid-etched titanium. The bacteriostatic ability of the alkali-treated titanium is proposed to result from the joint effect of micro/nanotopography and local pH increase at bacterium/material interface due to the hydrolysis of alkali (earth) metal titanate salts. The inhibitory action of cell proliferation is thought to be the effect of local pH increase at cell/material interface which causes the alkalosis of cells. This alkalosis model reported in this work will help to understand the biologic behaviors of various cells on alkali-treated titanium surface and design the intended biomedical applications. Copyright © 2014 Elsevier Inc. All rights reserved.

AFM Nanotools for Surgery of Biological Cells

Energy Technology Data Exchange (ETDEWEB)

Beard, J D; Gordeev, S N [Department of Physics, Claverton Down, University of Bath, Bath, BA2 7AY (United Kingdom); Guy, R H, E-mail: jdb28@bath.ac.uk [Department of Pharmacy and Pharmacology, Claverton Down, University of Bath, Bath, BA2 7AY (United Kingdom)

2011-03-01

Using a method of electron-beam induced deposition, we have been able to fabricate specialized AFM probes with application as 'nanotools' for the manipulation of biological structures ('nanosurgery'). We describe several such tools, including a 'nanoscalpel', 'nanoneedles' for probing intracellular structures, and a 'nanotome' which can separate surface layers from a biological structure. These applications are demonstrated by performing nanomanipulation on corneocyte cells from the outer layer of human skin.

Implications of Big Data for cell biology

OpenAIRE

Dolinski, Kara; Troyanskaya, Olga G.

2015-01-01

“Big Data” has surpassed “systems biology” and “omics” as the hottest buzzword in the biological sciences, but is there any substance behind the hype? Certainly, we have learned about various aspects of cell and molecular biology from the many individual high-throughput data sets that have been published in the past 15–20 years. These data, although useful as individual data sets, can provide much more knowledge when interrogated with Big Data approaches, such as applying integrative methods ...

Periodicity computation of generalized mathematical biology problems involving delay differential equations.

Science.gov (United States)

Jasim Mohammed, M; Ibrahim, Rabha W; Ahmad, M Z

2017-03-01

In this paper, we consider a low initial population model. Our aim is to study the periodicity computation of this model by using neutral differential equations, which are recognized in various studies including biology. We generalize the neutral Rayleigh equation for the third-order by exploiting the model of fractional calculus, in particular the Riemann-Liouville differential operator. We establish the existence and uniqueness of a periodic computational outcome. The technique depends on the continuation theorem of the coincidence degree theory. Besides, an example is presented to demonstrate the finding.

Computational methods for three-dimensional microscopy reconstruction

CERN Document Server

Frank, Joachim

2014-01-01

Approaches to the recovery of three-dimensional information on a biological object, which are often formulated or implemented initially in an intuitive way, are concisely described here based on physical models of the object and the image-formation process. Both three-dimensional electron microscopy and X-ray tomography can be captured in the same mathematical framework, leading to closely-related computational approaches, but the methodologies differ in detail and hence pose different challenges. The editors of this volume, Gabor T. Herman and Joachim Frank, are experts in the respective methodologies and present research at the forefront of biological imaging and structural biology.   Computational Methods for Three-Dimensional Microscopy Reconstruction will serve as a useful resource for scholars interested in the development of computational methods for structural biology and cell biology, particularly in the area of 3D imaging and modeling.

Fluid models and simulations of biological cell phenomena

Science.gov (United States)

Greenspan, H. P.

1982-01-01

The dynamics of coated droplets are examined within the context of biofluids. Of specific interest is the manner in which the shape of a droplet, the motion within it as well as that of aggregates of droplets can be controlled by the modulation of surface properties and the extent to which such fluid phenomena are an intrinsic part of cellular processes. From the standpoint of biology, an objective is to elucidate some of the general dynamical features that affect the disposition of an entire cell, cell colonies and tissues. Conventionally averaged field variables of continuum mechanics are used to describe the overall global effects which result from the myriad of small scale molecular interactions. An attempt is made to establish cause and effect relationships from correct dynamical laws of motion rather than by what may have been unnecessary invocation of metabolic or life processes. Several topics are discussed where there are strong analogies droplets and cells including: encapsulated droplets/cell membranes; droplet shape/cell shape; adhesion and spread of a droplet/cell motility and adhesion; and oams and multiphase flows/cell aggregates and tissues. Evidence is presented to show that certain concepts of continuum theory such as suface tension, surface free energy, contact angle, bending moments, etc. are relevant and applicable to the study of cell biology.

The Effects of 3D Computer Simulation on Biology Students' Achievement and Memory Retention

Science.gov (United States)

Elangovan, Tavasuria; Ismail, Zurida

2014-01-01

A quasi experimental study was conducted for six weeks to determine the effectiveness of two different 3D computer simulation based teaching methods, that is, realistic simulation and non-realistic simulation on Form Four Biology students' achievement and memory retention in Perak, Malaysia. A sample of 136 Form Four Biology students in Perak,…

A decade of molecular cell biology: achievements and challenges.

Science.gov (United States)

Akhtar, Asifa; Fuchs, Elaine; Mitchison, Tim; Shaw, Reuben J; St Johnston, Daniel; Strasser, Andreas; Taylor, Susan; Walczak, Claire; Zerial, Marino

2011-09-23

Nature Reviews Molecular Cell Biology celebrated its 10-year anniversary during this past year with a series of specially commissioned articles. To complement this, here we have asked researchers from across the field for their insights into how molecular cell biology research has evolved during this past decade, the key concepts that have emerged and the most promising interfaces that have developed. Their comments highlight the broad impact that particular advances have had, some of the basic understanding that we still require, and the collaborative approaches that will be essential for driving the field forward.

Molecular biological features of male germ cell differentiation

Science.gov (United States)

HIROSE, MIKA; TOKUHIRO, KEIZO; TAINAKA, HITOSHI; MIYAGAWA, YASUSHI; TSUJIMURA, AKIRA; OKUYAMA, AKIHIKO; NISHIMUNE, YOSHITAKE

2007-01-01

Somatic cell differentiation is required throughout the life of a multicellular organism to maintain homeostasis. In contrast, germ cells have only one specific function; to preserve the species by conveying the parental genes to the next generation. Recent studies of the development and molecular biology of the male germ cell have identified many genes, or isoforms, that are specifically expressed in the male germ cell. In the present review, we consider the unique features of male germ cell differentiation. (Reprod Med Biol 2007; 6: 1–9) PMID:29699260

Computer Literacy for Life Sciences: Helping the Digital-Era Biology Undergraduates Face Today's Research

Science.gov (United States)

Smolinski, Tomasz G.

2010-01-01

Computer literacy plays a critical role in today's life sciences research. Without the ability to use computers to efficiently manipulate and analyze large amounts of data resulting from biological experiments and simulations, many of the pressing questions in the life sciences could not be answered. Today's undergraduates, despite the ubiquity of…

Recent advances in hematopoietic stem cell biology

DEFF Research Database (Denmark)

Bonde, Jesper; Hess, David A; Nolta, Jan A

2004-01-01

PURPOSE OF REVIEW: Exciting advances have been made in the field of hematopoietic stem cell biology during the past year. This review summarizes recent progress in the identification, culture, and in vivo tracking of hematopoietic stem cells. RECENT FINDINGS: The roles of Wnt and Notch proteins...... in regulating stem cell renewal in the microenvironment, and how these molecules can be exploited in ex vivo stem cell culture, are reviewed. The importance of identification of stem cells using functional as well as phenotypic markers is discussed. The novel field of nanotechnology is then discussed...... in the context of stem cell tracking in vivo. This review concludes with a section on the unexpected potential of bone marrow-derived stem cells to contribute to the repair of damaged tissues. The contribution of cell fusion to explain the latter phenomenon is discussed. SUMMARY: Because of exciting discoveries...

Interdisciplinary research and education at the biology-engineering-computer science interface: a perspective.

Science.gov (United States)

Tadmor, Brigitta; Tidor, Bruce

2005-09-01

Progress in the life sciences, including genome sequencing and high-throughput experimentation, offers an opportunity for understanding biology and medicine from a systems perspective. This 'new view', which complements the more traditional component-based approach, involves the integration of biological research with approaches from engineering disciplines and computer science. The result is more than a new set of technologies. Rather, it promises a fundamental reconceptualization of the life sciences based on the development of quantitative and predictive models to describe crucial processes. To achieve this change, learning communities are being formed at the interface of the life sciences, engineering and computer science. Through these communities, research and education will be integrated across disciplines and the challenges associated with multidisciplinary team-based science will be addressed.

Cell-free synthetic biology for in vitro prototype engineering.

Science.gov (United States)

Moore, Simon J; MacDonald, James T; Freemont, Paul S

2017-06-15

Cell-free transcription-translation is an expanding field in synthetic biology as a rapid prototyping platform for blueprinting the design of synthetic biological devices. Exemplar efforts include translation of prototype designs into medical test kits for on-site identification of viruses (Zika and Ebola), while gene circuit cascades can be tested, debugged and re-designed within rapid turnover times. Coupled with mathematical modelling, this discipline lends itself towards the precision engineering of new synthetic life. The next stages of cell-free look set to unlock new microbial hosts that remain slow to engineer and unsuited to rapid iterative design cycles. It is hoped that the development of such systems will provide new tools to aid the transition from cell-free prototype designs to functioning synthetic genetic circuits and engineered natural product pathways in living cells. © 2017 The Author(s).

Highly Resolved Sub-Terahertz Vibrational Spectroscopy of Biological Macromolecules and Bacteria Cells

Science.gov (United States)

2016-07-01

HIGHLY RESOLVED SUB-TERAHERTZ VIBRATIONAL SPECTROSCOPY OF BIOLOGICAL MACROMOLECULES AND BACTERIA CELLS ECBC...SUBTITLE Highly Resolved Sub-Terahertz Vibrational Spectroscopy of Biological Macromolecules and Bacteria Cells 5a. CONTRACT NUMBER W911SR-14-P...22 4.3 Bacteria THz Study

Progress in Cell Marking for Synchrotron X-ray Computed Tomography

Science.gov (United States)

Hall, Christopher; Sturm, Erica; Schultke, Elisabeth; Arfelli, Fulvia; Menk, Ralf-Hendrik; Astolfo, Alberto; Juurlink, Bernhard H. J.

2010-07-01

Recently there has been an increase in research activity into finding ways of marking cells in live animals for pre-clinical trials. Development of certain drugs and other therapies crucially depend on tracking particular cells or cell types in living systems. Therefore cell marking techniques are required which will enable longitudinal studies, where individuals can be examined several times over the course of a therapy or study. The benefits of being able to study both disease and therapy progression in individuals, rather than cohorts are clear. The need for high contrast 3-D imaging, without harming or altering the biological system requires a non-invasive yet penetrating imaging technique. The technique will also have to provide an appropriate spatial and contrast resolution. X-ray computed tomography offers rapid acquisition of 3-D images and is set to become one of the principal imaging techniques in this area. Work by our group over the last few years has shown that marking cells with gold nano-particles (GNP) is an effective means of visualising marked cells in-vivo using x-ray CT. Here we report the latest results from these studies. Synchrotron X-ray CT images of brain lesions in rats taken using the SYRMEP facility at the Elettra synchrotron in 2009 have been compared with histological examination of the tissues. Some deductions are drawn about the visibility of the gold loaded cells in both light microscopy and x-ray imaging.

A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

Science.gov (United States)

Sung, Myong-Hee

2013-01-01

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

Applications of cell-free protein synthesis in synthetic biology: Interfacing bio-machinery with synthetic environments.

Science.gov (United States)

Lee, Kyung-Ho; Kim, Dong-Myung

2013-11-01

Synthetic biology is built on the synthesis, engineering, and assembly of biological parts. Proteins are the first components considered for the construction of systems with designed biological functions because proteins carry out most of the biological functions and chemical reactions inside cells. Protein synthesis is considered to comprise the most basic levels of the hierarchical structure of synthetic biology. Cell-free protein synthesis has emerged as a powerful technology that can potentially transform the concept of bioprocesses. With the ability to harness the synthetic power of biology without many of the constraints of cell-based systems, cell-free protein synthesis enables the rapid creation of protein molecules from diverse sources of genetic information. Cell-free protein synthesis is virtually free from the intrinsic constraints of cell-based methods and offers greater flexibility in system design and manipulability of biological synthetic machinery. Among its potential applications, cell-free protein synthesis can be combined with various man-made devices for rapid functional analysis of genomic sequences. This review covers recent efforts to integrate cell-free protein synthesis with various reaction devices and analytical platforms. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

New frontiers in human cell biology and medicine: can pluripotent stem cells deliver?

Science.gov (United States)

Goldstein, Lawrence S B

2012-11-12

Human pluripotent stem cells provide enormous opportunities to treat disease using cell therapy. But human stem cells can also drive biomedical and cell biological discoveries in a human model system, which can be directly linked to understanding disease or developing new therapies. Finally, rigorous scientific studies of these cells can and should inform the many science and medical policy issues that confront the translation of these technologies to medicine. In this paper, I discuss these issues using amyotrophic lateral sclerosis as an example.

ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus

OpenAIRE

Karp, P.D.; Berger, B.; Kovats, D.; Lengauer, T.; Linial, M.; Sabeti, P.; Hide, W.; Rost, B.

2015-01-01

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computati...

Induced hemocompatibility and bone formation as biological scaffold for cell therapy implant

Directory of Open Access Journals (Sweden)

Keng-Liang Ou

2016-06-01

Full Text Available Although stem cells can become almost any type of specialized cell in the human body and may have the potential to generate replacement cells for tissues and organs, the transplantation of these cells are hindered by immune rejection and teratoma formation. However, scientists have found a promising solution for these problems-they have discovered the ability to isolate stem cells from a patient’s umbilical cord blood or bone marrow. Even more recently, small stem cells, such as spore-like stem cells, Blastomere-Like Stem Cells (BLSCs, and Very-Small Embryonic-Like stem cells (VSELs isolated directly from the peripheral blood have beeninvestigated as a novel approach to stem cell therapy as they can be isolated directly from the peripheral blood. A newly-discovered population of multipotent stem cells in this class has been dubbed StemBios (SB cells. The potential therapeutic uses of such stem cells have been explored in many ways, one of which includes dental remodeling and construction. Using adult stem cells, scientists have engineered and cultivated teeth in mice that may one day be used for human implantation.It follows that such regeneration may be possible, to a certain degree, in human patients as well. This idea leads to the present study on the effect of SB cell therapy on early osseointegrationof dental implants. Titanium (Ti dental implants have been proven to be a reliable and predictable treatment for restoration of edentulous regions. The osseointegration process can be described in two stages: primary stability (mechanical stability and secondary stability (biological stability. The mechanical stabilization of the implant reflects the interaction between the bone density and the features of the implant designs and can be determined after implant insertion. Alternatively,the biological stabilization of the implant is a physiologic healing process. It is couple to the biological interaction between the external surface of the

Cancer stem cells in hepatocellular carcinoma: Therapeutic implications based on stem cell biology.

Science.gov (United States)

Chiba, Tetsuhiro; Iwama, Atsushi; Yokosuka, Osamu

2016-01-01

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third most frequent cause of cancer-related death worldwide. Despite advances in its diagnosis and treatment, the prognosis of patients with advanced HCC remains unfavorable. Recent advances in stem cell biology and associated technologies have enabled the identification of minor components of tumorigenic cells, termed cancer stem cells (CSC) or tumor-initiating cells, in cancers such as HCC. Furthermore, because CSC play a central role in tumor development, metastasis and recurrence, they are considered to be a therapeutic target in cancer treatment. Hepatic CSC have been successfully identified using functional and cell surface markers. The analysis of purified hepatic CSC has revealed the molecular machinery and signaling pathways involved in their maintenance. In addition, epigenetic transcriptional regulation has been shown to be important in the development and maintenance of CSC. Although inhibitors of CSC show promise as CSC-targeting drugs, novel therapeutic approaches for the eradication of CSC are yet to be established. In this review, we describe recent progress in hepatic CSC research and provide a perspective on the available therapeutic approaches based on stem cell biology. © 2015 The Japan Society of Hepatology.

Quantitative computational models of molecular self-assembly in systems biology.

Science.gov (United States)

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Perturbation biology nominates upstream-downstream drug combinations in RAF inhibitor resistant melanoma cells.

Science.gov (United States)

Korkut, Anil; Wang, Weiqing; Demir, Emek; Aksoy, Bülent Arman; Jing, Xiaohong; Molinelli, Evan J; Babur, Özgün; Bemis, Debra L; Onur Sumer, Selcuk; Solit, David B; Pratilas, Christine A; Sander, Chris

2015-08-18

Resistance to targeted cancer therapies is an important clinical problem. The discovery of anti-resistance drug combinations is challenging as resistance can arise by diverse escape mechanisms. To address this challenge, we improved and applied the experimental-computational perturbation biology method. Using statistical inference, we build network models from high-throughput measurements of molecular and phenotypic responses to combinatorial targeted perturbations. The models are computationally executed to predict the effects of thousands of untested perturbations. In RAF-inhibitor resistant melanoma cells, we measured 143 proteomic/phenotypic entities under 89 perturbation conditions and predicted c-Myc as an effective therapeutic co-target with BRAF or MEK. Experiments using the BET bromodomain inhibitor JQ1 affecting the level of c-Myc protein and protein kinase inhibitors targeting the ERK pathway confirmed the prediction. In conclusion, we propose an anti-cancer strategy of co-targeting a specific upstream alteration and a general downstream point of vulnerability to prevent or overcome resistance to targeted drugs.

Biomaterials and computation: a strategic alliance to investigate emergent responses of neural cells.

Science.gov (United States)

Sergi, Pier Nicola; Cavalcanti-Adam, Elisabetta Ada

2017-03-28

Topographical and chemical cues drive migration, outgrowth and regeneration of neurons in different and crucial biological conditions. In the natural extracellular matrix, their influences are so closely coupled that they result in complex cellular responses. As a consequence, engineered biomaterials are widely used to simplify in vitro conditions, disentangling intricate in vivo behaviours, and narrowing the investigation on particular emergent responses. Nevertheless, how topographical and chemical cues affect the emergent response of neural cells is still unclear, thus in silico models are used as additional tools to reproduce and investigate the interactions between cells and engineered biomaterials. This work aims at presenting the synergistic use of biomaterials-based experiments and computation as a strategic way to promote the discovering of complex neural responses as well as to allow the interactions between cells and biomaterials to be quantitatively investigated, fostering a rational design of experiments.

High-dimensional single-cell cancer biology.

Science.gov (United States)

Irish, Jonathan M; Doxie, Deon B

2014-01-01

Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.

Multidisciplinary approaches to understanding collective cell migration in developmental biology.

Science.gov (United States)

Schumacher, Linus J; Kulesa, Paul M; McLennan, Rebecca; Baker, Ruth E; Maini, Philip K

2016-06-01

Mathematical models are becoming increasingly integrated with experimental efforts in the study of biological systems. Collective cell migration in developmental biology is a particularly fruitful application area for the development of theoretical models to predict the behaviour of complex multicellular systems with many interacting parts. In this context, mathematical models provide a tool to assess the consistency of experimental observations with testable mechanistic hypotheses. In this review, we showcase examples from recent years of multidisciplinary investigations of neural crest cell migration. The neural crest model system has been used to study how collective migration of cell populations is shaped by cell-cell interactions, cell-environmental interactions and heterogeneity between cells. The wide range of emergent behaviours exhibited by neural crest cells in different embryonal locations and in different organisms helps us chart out the spectrum of collective cell migration. At the same time, this diversity in migratory characteristics highlights the need to reconcile or unify the array of currently hypothesized mechanisms through the next generation of experimental data and generalized theoretical descriptions. © 2016 The Authors.

The biologic effects of cigarette smoke on cancer cells.

Science.gov (United States)

Sobus, Samantha L; Warren, Graham W

2014-12-01

Smoking is one of the largest preventable risk factors for developing cancer, and continued smoking by cancer patients is associated with increased toxicity, recurrence, risk of second primary cancer, and mortality. Cigarette smoke (CS) contains thousands of chemicals, including many known carcinogens. The carcinogenic effects of CS are well established, but relatively little work has been done to evaluate the effects of CS on cancer cells. In this review of the literature, the authors demonstrate that CS induces a more malignant tumor phenotype by increasing proliferation, migration, invasion, and angiogenesis and by activating prosurvival cellular pathways. Significant work is needed to understand the biologic effect of CS on cancer biology, including the development of model systems and the identification of critical biologic mediators of CS-induced changes in cancer cell physiology. © 2014 American Cancer Society.

Special Issue: International Congress of Cell Biology 2016, Prague

Czech Academy of Sciences Publication Activity Database

Stick, R.; Dráber, Pavel

2017-01-01

Roč. 254, č. 3 (2017), s. 1141-1142 ISSN 0033-183X R&D Projects: GA ČR GA16-25159S Institutional support: RVO:68378050 Keywords : cellular structures and functions, ,, , * tubulin isotypes * actin * transcription regulation * signaling pathways Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Cell biology Impact factor: 2.870, year: 2016

Synthetic biology in cell-based cancer immunotherapy.

Science.gov (United States)

Chakravarti, Deboki; Wong, Wilson W

2015-08-01

The adoptive transfer of genetically engineered T cells with cancer-targeting receptors has shown tremendous promise for eradicating tumors in clinical trials. This form of cellular immunotherapy presents a unique opportunity to incorporate advanced systems and synthetic biology approaches to create cancer therapeutics with novel functions. We first review the development of synthetic receptors, switches, and circuits to control the location, duration, and strength of T cell activity against tumors. In addition, we discuss the cellular engineering and genome editing of host cells (or the chassis) to improve the efficacy of cell-based cancer therapeutics, and to reduce the time and cost of manufacturing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Tumor necrosis factor (TNF) biology and cell death.

Science.gov (United States)

Bertazza, Loris; Mocellin, Simone

2008-01-01

Tumor necrosis factor (TNF) was the first cytokine to be used in humans for cancer therapy. However, its role in the treatment of cancer patients is debated. Most uncertainties in this field stem from the knowledge that the pathways directly activated or indirectly affected upon TNF engagement with its receptors can ultimately lead to very different outcomes in terms of cell survival. In this article, we summarize the fundamental molecular biology aspects of this cytokine. Such a basis is a prerequisite to critically approach the sometimes conflicting preclinical and clinical findings regarding the relationship between TNF, tumor biology and anticancer therapy. Although the last decade has witnessed remarkable advances in this field, we still do not know in detail how cells choose between life and death after TNF stimulation. Understanding this mechanism will not only shed new light on the physiological significance of TNF-driven programmed cell death but also help investigators maximize the anticancer potential of this cytokine.

Unleashing the potential of the root hair cell as a single plant cell type model in root systems biology

Directory of Open Access Journals (Sweden)

Zhenzhen eQiao

2013-11-01

Full Text Available Plant root is an organ composed of multiple cell types with different functions. This multicellular complexity limits our understanding of root biology because –omics studies performed at the level of the entire root reflect the average responses of all cells composing the organ. To overcome this difficulty and allow a more comprehensive understanding of root cell biology, an approach is needed that would focus on one single cell type in the plant root. Because of its biological functions (i.e. uptake of water and various nutrients; primary site of infection by nitrogen-fixing bacteria in legumes, the root hair cell is an attractive single cell model to study root cell response to various stresses and treatments. To fully study their biology, we have recently optimized procedures in obtaining root hair cell samples. We culture the plants using an ultrasound aeroponic system maximizing root hair cell density on the entire root systems and allowing the homogeneous treatment of the root system. We then isolate the root hair cells in liquid nitrogen. Isolated root hair yields could be up to 800 to 1000 mg of plant cells from 60 root systems. Using soybean as a model, the purity of the root hair was assessed by comparing the expression level of genes previously identified as soybean root hair specific between preparations of isolated root hair cells and stripped roots, roots devoid in root hairs. Enlarging our tests to include other plant species, our results support the isolation of large quantities of highly purified root hair cells which is compatible with a systems biology approach.

Agent-based modelling in synthetic biology.

Science.gov (United States)

Gorochowski, Thomas E

2016-11-30

Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).

Heavy ion induced DNA transfer in biological cells

International Nuclear Information System (INIS)

Vilaithong, T.; Yu, L.D.; Apavatjrut, P.; Phanchaisri, B.; Sangyuenyongpipat, S.; Anuntalabhochai, S.; Brown, I.G.

2004-01-01

Low-energy ion beam bombardment of biological materials for genetic modification purposes has experienced rapid growth in the last decade, particularly for the direct DNA transfer into living organisms including both plants and bacteria. Attempts have been made to understand the mechanisms involved in ion-bombardment-induced direct gene transfer into biological cells. Here we summarize the present status of the application of low-energy ions for genetic modification of living sample materials

In Silico Dynamics: computer simulation in a Virtual Embryo ...

Science.gov (United States)

Abstract: Utilizing cell biological information to predict higher order biological processes is a significant challenge in predictive toxicology. This is especially true for highly dynamical systems such as the embryo where morphogenesis, growth and differentiation require precisely orchestrated interactions between diverse cell populations. In patterning the embryo, genetic signals setup spatial information that cells then translate into a coordinated biological response. This can be modeled as ‘biowiring diagrams’ representing genetic signals and responses. Because the hallmark of multicellular organization resides in the ability of cells to interact with one another via well-conserved signaling pathways, multiscale computational (in silico) models that enable these interactions provide a platform to translate cellular-molecular lesions perturbations into higher order predictions. Just as ‘the Cell’ is the fundamental unit of biology so too should it be the computational unit (‘Agent’) for modeling embryogenesis. As such, we constructed multicellular agent-based models (ABM) with ‘CompuCell3D’ (www.compucell3d.org) to simulate kinematics of complex cell signaling networks and enable critical tissue events for use in predictive toxicology. Seeding the ABMs with HTS/HCS data from ToxCast demonstrated the potential to predict, quantitatively, the higher order impacts of chemical disruption at the cellular or biochemical level. This is demonstrate

Micro and nano-platforms for biological cell analysis

DEFF Research Database (Denmark)

Svendsen, Winnie Edith; Castillo, Jaime; Moresco, Jacob Lange

2011-01-01

In this paper some technological platforms developed for biological cell analysis will be presented and compared to existing systems. In brief, we present a novel micro cell culture chamber based on diffusion feeding of cells, into which cells can be introduced and extracted after culturing using...... from the cells, while passive modifications involve the presence of a peptide nanotube based scaffold for the cell culturing that mimics the in vivo environment. Two applications involving fluorescent in situ hybridization (FISH) analysis and cancer cell sorting are presented, as examples of further...... analysis that can be done after cell culturing. A platform able to automate the entire process from cell culturing to cell analysis by means of simple plug and play of various self-contained, individually fabricated modules is finally described....

Discovering biological progression underlying microarray samples.

Directory of Open Access Journals (Sweden)

Peng Qiu

2011-04-01

Full Text Available In biological systems that undergo processes such as differentiation, a clear concept of progression exists. We present a novel computational approach, called Sample Progression Discovery (SPD, to discover patterns of biological progression underlying microarray gene expression data. SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression, and that each sample represents one unknown point along the progression of that process. SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression. We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression, without providing SPD any information of the underlying process. When applied to a cell cycle time series microarray dataset, SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated, yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle. When applied to B-cell differentiation data, SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB. When applied to mouse embryonic stem cell differentiation data, SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes. When applied to a prostate cancer microarray dataset, SPD identified gene modules that reflect a progression consistent with disease stages. SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the

An interdepartmental Ph.D. program in computational biology and bioinformatics: the Yale perspective.

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Gerstein, Mark; Greenbaum, Dov; Cheung, Kei; Miller, Perry L

2007-02-01

Computational biology and bioinformatics (CBB), the terms often used interchangeably, represent a rapidly evolving biological discipline. With the clear potential for discovery and innovation, and the need to deal with the deluge of biological data, many academic institutions are committing significant resources to develop CBB research and training programs. Yale formally established an interdepartmental Ph.D. program in CBB in May 2003. This paper describes Yale's program, discussing the scope of the field, the program's goals and curriculum, as well as a number of issues that arose in implementing the program. (Further updated information is available from the program's website, www.cbb.yale.edu.)

Large Scale Computing and Storage Requirements for Biological and Environmental Research

Energy Technology Data Exchange (ETDEWEB)

DOE Office of Science, Biological and Environmental Research Program Office (BER),

2009-09-30

In May 2009, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR), and DOE's Office of Biological and Environmental Research (BER) held a workshop to characterize HPC requirements for BER-funded research over the subsequent three to five years. The workshop revealed several key points, in addition to achieving its goal of collecting and characterizing computing requirements. Chief among them: scientific progress in BER-funded research is limited by current allocations of computational resources. Additionally, growth in mission-critical computing -- combined with new requirements for collaborative data manipulation and analysis -- will demand ever increasing computing, storage, network, visualization, reliability and service richness from NERSC. This report expands upon these key points and adds others. It also presents a number of"case studies" as significant representative samples of the needs of science teams within BER. Workshop participants were asked to codify their requirements in this"case study" format, summarizing their science goals, methods of solution, current and 3-5 year computing requirements, and special software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel,"multi-core" environment that is expected to dominate HPC architectures over the next few years.

Using Femtosecond Laser Subcellular Surgery as a Tool to Study Cell Biology

Energy Technology Data Exchange (ETDEWEB)

Shen, N; Colvin, M E; Huser, T

2007-02-27

Research on cellular function and regulation would be greatly advanced by new instrumentation using methods to alter cellular processes with spatial discrimination on the nanometer-scale. We present a novel technique for targeting submicrometer sized organelles or other biologically important regions in living cells using femtosecond laser pulses. By tightly focusing these pulses beneath the cell membrane, we can vaporize cellular material inside the cell through nonlinear optical processes. This technique enables non-invasive manipulation of the physical structure of a cell with sub-micrometer resolution. We propose to study the role mitochondria play in cell proliferation and apoptosis. Our technique provides a unique tool for the study of cell biology.

Derivation and computation of discrete-delay and continuous-delay SDEs in mathematical biology.

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Allen, Edward J

2014-06-01

Stochastic versions of several discrete-delay and continuous-delay differential equations, useful in mathematical biology, are derived from basic principles carefully taking into account the demographic, environmental, or physiological randomness in the dynamic processes. In particular, stochastic delay differential equation (SDDE) models are derived and studied for Nicholson's blowflies equation, Hutchinson's equation, an SIS epidemic model with delay, bacteria/phage dynamics, and glucose/insulin levels. Computational methods for approximating the SDDE models are described. Comparisons between computational solutions of the SDDEs and independently formulated Monte Carlo calculations support the accuracy of the derivations and of the computational methods.

Biological Dynamics Markup Language (BDML): an open format for representing quantitative biological dynamics data.

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Kyoda, Koji; Tohsato, Yukako; Ho, Kenneth H L; Onami, Shuichi

2015-04-01

Recent progress in live-cell imaging and modeling techniques has resulted in generation of a large amount of quantitative data (from experimental measurements and computer simulations) on spatiotemporal dynamics of biological objects such as molecules, cells and organisms. Although many research groups have independently dedicated their efforts to developing software tools for visualizing and analyzing these data, these tools are often not compatible with each other because of different data formats. We developed an open unified format, Biological Dynamics Markup Language (BDML; current version: 0.2), which provides a basic framework for representing quantitative biological dynamics data for objects ranging from molecules to cells to organisms. BDML is based on Extensible Markup Language (XML). Its advantages are machine and human readability and extensibility. BDML will improve the efficiency of development and evaluation of software tools for data visualization and analysis. A specification and a schema file for BDML are freely available online at http://ssbd.qbic.riken.jp/bdml/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Delivering The Benefits of Chemical-Biological Integration in Computational Toxicology at the EPA (ACS Fall meeting)

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Abstract: Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intent...

Clinical relevance and biology of circulating tumor cells

Science.gov (United States)

2011-01-01

Most breast cancer patients die due to metastases, and the early onset of this multistep process is usually missed by current tumor staging modalities. Therefore, ultrasensitive techniques have been developed to enable the enrichment, detection, isolation and characterization of disseminated tumor cells in bone marrow and circulating tumor cells in the peripheral blood of cancer patients. There is increasing evidence that the presence of these cells is associated with an unfavorable prognosis related to metastatic progression in the bone and other organs. This review focuses on investigations regarding the biology and clinical relevance of circulating tumor cells in breast cancer. PMID:22114869

Graphene liquid cells for multi-technique analysis of biological cells in water environment

Science.gov (United States)

Matruglio, A.; Zucchiatti, P.; Birarda, G.; Marmiroli, B.; D'Amico, F.; Kocabas, C.; Kiskinova, M.; Vaccari, L.

2018-05-01

In-cell exploration of biomolecular constituents is the new frontier of cellular biology that will allow full access to structure-activity correlation of biomolecules, overcoming the limitations imposed by dissecting the cellular milieu. However, the presence of water, which is a very strong IR absorber and incompatible with the vacuum working conditions of all analytical methods using soft x-rays and electrons, poses severe constraint to perform important imaging and spectroscopic analyses under physiological conditions. Recent advances to separate the sample compartment in liquid cell are based on electron and photon transparent but molecular-impermeable graphene membranes. This strategy has opened a unique opportunity to explore technological materials under realistic operation conditions using various types of electron microscopy. However, the widespread of the graphene liquid cell applications is still impeded by the lack of well-established approaches for their massive production. We report on the first preliminary results for the fabrication of reproducible graphene liquid cells appropriate for the analysis of biological specimens in their natural hydrated environment with several crucial analytical techniques, namely FTIR microscopy, Raman spectroscopy, AFM, SEM and TEM.

Computational cell model based on autonomous cell movement regulated by cell-cell signalling successfully recapitulates the "inside and outside" pattern of cell sorting

Directory of Open Access Journals (Sweden)

Ajioka Itsuki

2007-09-01

Full Text Available Abstract Background Development of multicellular organisms proceeds from a single fertilized egg as the combined effect of countless numbers of cellular interactions among highly dynamic cells. Since at least a reminiscent pattern of morphogenesis can be recapitulated in a reproducible manner in reaggregation cultures of dissociated embryonic cells, which is known as cell sorting, the cells themselves must possess some autonomous cell behaviors that assure specific and reproducible self-organization. Understanding of this self-organized dynamics of heterogeneous cell population seems to require some novel approaches so that the approaches bridge a gap between molecular events and morphogenesis in developmental and cell biology. A conceptual cell model in a computer may answer that purpose. We constructed a dynamical cell model based on autonomous cell behaviors, including cell shape, growth, division, adhesion, transformation, and motility as well as cell-cell signaling. The model gives some insights about what cellular behaviors make an appropriate global pattern of the cell population. Results We applied the model to "inside and outside" pattern of cell-sorting, in which two different embryonic cell types within a randomly mixed aggregate are sorted so that one cell type tends to gather in the central region of the aggregate and the other cell type surrounds the first cell type. Our model can modify the above cell behaviors by varying parameters related to them. We explored various parameter sets with which the "inside and outside" pattern could be achieved. The simulation results suggested that direction of cell movement responding to its neighborhood and the cell's mobility are important for this specific rearrangement. Conclusion We constructed an in silico cell model that mimics autonomous cell behaviors and applied it to cell sorting, which is a simple and appropriate phenomenon exhibiting self-organization of cell population. The model

Toward synthesizing executable models in biology.

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Fisher, Jasmin; Piterman, Nir; Bodik, Rastislav

2014-01-01

Over the last decade, executable models of biological behaviors have repeatedly provided new scientific discoveries, uncovered novel insights, and directed new experimental avenues. These models are computer programs whose execution mechanistically simulates aspects of the cell's behaviors. If the observed behavior of the program agrees with the observed biological behavior, then the program explains the phenomena. This approach has proven beneficial for gaining new biological insights and directing new experimental avenues. One advantage of this approach is that techniques for analysis of computer programs can be applied to the analysis of executable models. For example, one can confirm that a model agrees with experiments for all possible executions of the model (corresponding to all environmental conditions), even if there are a huge number of executions. Various formal methods have been adapted for this context, for example, model checking or symbolic analysis of state spaces. To avoid manual construction of executable models, one can apply synthesis, a method to produce programs automatically from high-level specifications. In the context of biological modeling, synthesis would correspond to extracting executable models from experimental data. We survey recent results about the usage of the techniques underlying synthesis of computer programs for the inference of biological models from experimental data. We describe synthesis of biological models from curated mutation experiment data, inferring network connectivity models from phosphoproteomic data, and synthesis of Boolean networks from gene expression data. While much work has been done on automated analysis of similar datasets using machine learning and artificial intelligence, using synthesis techniques provides new opportunities such as efficient computation of disambiguating experiments, as well as the ability to produce different kinds of models automatically from biological data.

SIRT6 knockout cells resist apoptosis initiation but not progression: a computational method to evaluate the progression of apoptosis.

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Domanskyi, Sergii; Nicholatos, Justin W; Schilling, Joshua E; Privman, Vladimir; Libert, Sergiy

2017-11-01

Apoptosis is essential for numerous processes, such as development, resistance to infections, and suppression of tumorigenesis. Here, we investigate the influence of the nutrient sensing and longevity-assuring enzyme SIRT6 on the dynamics of apoptosis triggered by serum starvation. Specifically, we characterize the progression of apoptosis in wild type and SIRT6 deficient mouse embryonic fibroblasts using time-lapse flow cytometry and computational modelling based on rate-equations and cell distribution analysis. We find that SIRT6 deficient cells resist apoptosis by delaying its initiation. Interestingly, once apoptosis is initiated, the rate of its progression is higher in SIRT6 null cells compared to identically cultured wild type cells. However, SIRT6 null cells succumb to apoptosis more slowly, not only in response to nutrient deprivation but also in response to other stresses. Our data suggest that SIRT6 plays a role in several distinct steps of apoptosis. Overall, we demonstrate the utility of our computational model to describe stages of apoptosis progression and the integrity of the cellular membrane. Such measurements will be useful in a broad range of biological applications.

Cell biology, biophysics, and mechanobiology: From the basics to Clinics.

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Zeng, Y

2017-04-29

Cell biology, biomechanics and biophysics are the key subjects that guide our understanding in diverse areas of tissue growth, development, remodeling and homeostasis. Novel discoveries such as molecular mechanism, and mechanobiological mechanism in cell biology, biomechanics and biophysics play essential roles in our understanding of the pathogenesis of various human diseases, as well as in designing the treatment of these diseases. In addition, studies in these areas will also facilitate early diagnostics of human diseases, such as cardiovascular diseases and cancer. In this special issue, we collected 10 original research articles and 1 review...

[The implementation of computer model in research of dynamics of proliferation of cells of thyroid gland follicle].

Science.gov (United States)

Abduvaliev, A A; Gil'dieva, M S; Khidirov, B N; Saĭdalieva, M; Khasanov, A A; Musaeva, Sh N; Saatov, T S

2012-04-01

The article deals with the results of computational experiments in research of dynamics of proliferation of cells of thyroid gland follicle in normal condition and in the case of malignant neoplasm. The model studies demonstrated that the chronic increase of parameter of proliferation of cells of thyroid gland follicle results in abnormal behavior of numbers of cell cenosis of thyroid gland follicle. The stationary state interrupts, the auto-oscillations occur with transition to irregular oscillations with unpredictable cell proliferation and further to the "black hole" effect. It is demonstrated that the present medical biologic experimental data and theory propositions concerning the structural functional organization of thyroid gland on cell level permit to develop mathematical models for quantitative analysis of numbers of cell cenosis of thyroid gland follicle in normal conditions. The technique of modeling of regulative mechanisms of living systems and equations of cell cenosis regulations was used

Physical properties of biological entities: an introduction to the ontology of physics for biology.

Directory of Open Access Journals (Sweden)

Daniel L Cook

Full Text Available As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of physical properties-energies, volumes, flow rates-of those entities. In this paper, we introduce the Ontology of Physics for Biology (OPB, a reference ontology of classical physics designed for annotating biophysical content of growing repositories of biomedical datasets and analytical models. The OPB's semantic framework, traceable to James Clerk Maxwell, encompasses modern theories of system dynamics and thermodynamics, and is implemented as a computational ontology that references available upper ontologies. In this paper we focus on the OPB classes that are designed for annotating physical properties encoded in biomedical datasets and computational models, and we discuss how the OPB framework will facilitate biomedical knowledge integration.

Physical properties of biological entities: an introduction to the ontology of physics for biology.

Science.gov (United States)

Cook, Daniel L; Bookstein, Fred L; Gennari, John H

2011-01-01

As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of physical properties-energies, volumes, flow rates-of those entities. In this paper, we introduce the Ontology of Physics for Biology (OPB), a reference ontology of classical physics designed for annotating biophysical content of growing repositories of biomedical datasets and analytical models. The OPB's semantic framework, traceable to James Clerk Maxwell, encompasses modern theories of system dynamics and thermodynamics, and is implemented as a computational ontology that references available upper ontologies. In this paper we focus on the OPB classes that are designed for annotating physical properties encoded in biomedical datasets and computational models, and we discuss how the OPB framework will facilitate biomedical knowledge integration. © 2011 Cook et al.

The Histochemistry and Cell Biology omnium-gatherum: the year 2015 in review.

Science.gov (United States)

Taatjes, Douglas J; Roth, Jürgen

2016-03-01

We provide here our annual review/synopsis of all of the articles published in Histochemistry and Cell Biology (HCB) for the preceding year. In 2015, HCB published 102 articles, representing a wide variety of topics and methodologies. For ease of access to these differing topics, we have created categories, as determined by the types of articles presented to provide a quick index representing the general areas covered. This year, these categories include: (1) advances in methodologies; (2) molecules in health and disease; (3) organelles, subcellular structures, and compartments; (4) the nucleus; (5) stem cells and tissue engineering; (6) cell cultures: properties and capabilities; (7) connective tissues and extracellular matrix; (8) developmental biology; (9) nervous system; (10) musculoskeletal system; (11) respiratory and cardiovascular system; (12) liver and gastrointestinal tract; and (13) male and female reproductive systems. Of note, the categories proceed from methods development, to molecules, intracellular compartments, stem cells and cell culture, extracellular matrix, developmental biology, and finishing with various organ systems, hopefully presenting a logical journey from methods to organismal molecules, cells, and whole tissue systems.

100 years after Smoluchowski: stochastic processes in cell biology

International Nuclear Information System (INIS)

Holcman, D; Schuss, Z

2017-01-01

100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation. (topical review)

Unravelling biology and shifting paradigms in cancer with single-cell sequencing.

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Baslan, Timour; Hicks, James

2017-08-24

The fundamental operative unit of a cancer is the genetically and epigenetically innovative single cell. Whether proliferating or quiescent, in the primary tumour mass or disseminated elsewhere, single cells govern the parameters that dictate all facets of the biology of cancer. Thus, single-cell analyses provide the ultimate level of resolution in our quest for a fundamental understanding of this disease. Historically, this quest has been hampered by technological shortcomings. In this Opinion article, we argue that the rapidly evolving field of single-cell sequencing has unshackled the cancer research community of these shortcomings. From furthering an elemental understanding of intra-tumoural genetic heterogeneity and cancer genome evolution to illuminating the governing principles of disease relapse and metastasis, we posit that single-cell sequencing promises to unravel the biology of all facets of this disease.

Applied Developmental Biology: Making Human Pancreatic Beta Cells for Diabetics.

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Melton, Douglas A

2016-01-01

Understanding the genes and signaling pathways that determine the differentiation and fate of a cell is a central goal of developmental biology. Using that information to gain mastery over the fates of cells presents new approaches to cell transplantation and drug discovery for human diseases including diabetes. © 2016 Elsevier Inc. All rights reserved.

Crosstalk between stromal cells and cancer cells in pancreatic cancer: New insights into stromal biology.

Science.gov (United States)

Zhan, Han-Xiang; Zhou, Bin; Cheng, Yu-Gang; Xu, Jian-Wei; Wang, Lei; Zhang, Guang-Yong; Hu, San-Yuan

2017-04-28

Pancreatic cancer (PC) remains one of the most lethal malignancies worldwide. Increasing evidence has confirmed the pivotal role of stromal components in the regulation of carcinogenesis, invasion, metastasis, and therapeutic resistance in PC. Interaction between neoplastic cells and stromal cells builds a specific microenvironment, which further modulates the malignant properties of cancer cells. Instead of being a "passive bystander", stroma may play a role as a "partner in crime" in PC. However, the role of stromal components in PC is complex and requires further investigation. In this article, we review recent advances regarding the regulatory roles and mechanisms of stroma biology, especially the cellular components such as pancreatic stellate cells, macrophages, neutrophils, adipocytes, epithelial cells, pericytes, mast cells, and lymphocytes, in PC. Crosstalk between stromal cells and cancer cells is thoroughly investigated. We also review the prognostic value and molecular therapeutic targets of stroma in PC. This review may help us further understand the molecular mechanisms of stromal biology and its role in PC development and therapeutic resistance. Moreover, targeting stroma components may provide new therapeutic strategies for this stubborn disease. Copyright © 2017 Elsevier B.V. All rights reserved.

Proteomics in studying cancer stem cell biology.

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Kranenburg, Onno; Emmink, Benjamin L; Knol, Jaco; van Houdt, Winan J; Rinkes, Inne H M Borel; Jimenez, Connie R

2012-06-01

Normal multipotent tissue stem cells (SCs) are the driving force behind tissue turnover and repair. The cancer stem cell theory holds that tumors also contain stem-like cells that drive tumor growth and metastasis formation. However, very little is known about the regulation of SC maintenance pathways in cancer and how these are affected by cancer-specific genetic alterations and by treatment. Proteomics is emerging as a powerful tool to identify the signaling complexes and pathways that control multi- and pluri-potency and SC differentiation. Here, the authors review the novel insights that these studies have provided and present a comprehensive strategy for the use of proteomics in studying cancer SC biology.

After the Greeting: Realizing the Potential of Physical Models in Cell Biology.

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Paluch, Ewa K

2015-12-01

Biophysics is increasingly taking center stage in cell biology as the tools for precise quantifications of cellular behaviors expand. Interdisciplinary approaches, combining quantitative physical modeling with cell biology, are of growing interest to journal editors, funding agencies, and hiring committees. However, despite an ever-increasing emphasis on the importance of interdisciplinary research, the student trained in biology may still be at a loss as to what it actually means. I discuss here some considerations on how to achieve meaningful and high-quality interdisciplinary work. Copyright © 2015 Elsevier Ltd. All rights reserved.

In search of mitochondrial mechanisms: interfield excursions between cell biology and biochemistry.

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Bechtel, William; Abrahamsen, Adele

2007-01-01

Developing models of biological mechanisms, such as those involved in respiration in cells, often requires collaborative effort drawing upon techniques developed and information generated in different disciplines. Biochemists in the early decades of the 20th century uncovered all but the most elusive chemical operations involved in cellular respiration, but were unable to align the reaction pathways with particular structures in the cell. During the period 1940-1965 cell biology was emerging as a new discipline and made distinctive contributions to understanding the role of the mitochondrion and its component parts in cellular respiration. In particular, by developing techniques for localizing enzymes or enzyme systems in specific cellular components, cell biologists provided crucial information about the organized structures in which the biochemical reactions occurred. Although the idea that biochemical operations are intimately related to and depend on cell structures was at odds with the then-dominant emphasis on systems of soluble enzymes in biochemistry, a reconceptualization of energetic processes in the 1960s and 1970s made it clear why cell structure was critical to the biochemical account. This paper examines how numerous excursions between biochemistry and cell biology contributed a new understanding of the mechanism of cellular respiration.

Models to Study NK Cell Biology and Possible Clinical Application.

Science.gov (United States)

Zamora, Anthony E; Grossenbacher, Steven K; Aguilar, Ethan G; Murphy, William J

2015-08-03

Natural killer (NK) cells are large granular lymphocytes of the innate immune system, responsible for direct targeting and killing of both virally infected and transformed cells. NK cells rapidly recognize and respond to abnormal cells in the absence of prior sensitization due to their wide array of germline-encoded inhibitory and activating receptors, which differs from the receptor diversity found in B and T lymphocytes that is due to the use of recombination-activation gene (RAG) enzymes. Although NK cells have traditionally been described as natural killers that provide a first line of defense prior to the induction of adaptive immunity, a more complex view of NK cells is beginning to emerge, indicating they may also function in various immunoregulatory roles and have the capacity to shape adaptive immune responses. With the growing appreciation for the diverse functions of NK cells, and recent technological advancements that allow for a more in-depth understanding of NK cell biology, we can now begin to explore new ways to manipulate NK cells to increase their clinical utility. In this overview unit, we introduce the reader to various aspects of NK cell biology by reviewing topics ranging from NK cell diversity and function, mouse models, and the roles of NK cells in health and disease, to potential clinical applications. © 2015 by John Wiley & Sons, Inc. Copyright © 2015 John Wiley & Sons, Inc.

Biological Influence of Deuterium on Procariotic and Eukaryotic Cells

OpenAIRE

Oleg Mosin; Ignat Ignatov

2014-01-01

Biologic influence of deuterium (D) on cells of various taxonomic groups of prokaryotic and eukaryotic microorganisms realizing methylotrophic, chemoheterotrophic, photo-organotrophic, and photosynthetic ways of assimilation of carbon substrates are investigated at growth on media with heavy water (D2О). The method of step by step adaptation technique of cells to D2О was developed, consisting in plating of cells on 2 % agarose nutrient media containing increasing gradient of concentration of ...

Machine learning and computer vision approaches for phenotypic profiling.

Science.gov (United States)

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

Scale-free flow of life: on the biology, economics, and physics of the cell

Directory of Open Access Journals (Sweden)

Kurakin Alexei

2009-05-01

Full Text Available Abstract The present work is intended to demonstrate that most of the paradoxes, controversies, and contradictions accumulated in molecular and cell biology over many years of research can be readily resolved if the cell and living systems in general are re-interpreted within an alternative paradigm of biological organization that is based on the concepts and empirical laws of nonequilibrium thermodynamics. In addition to resolving paradoxes and controversies, the proposed re-conceptualization of the cell and biological organization reveals hitherto unappreciated connections among many seemingly disparate phenomena and observations, and provides new and powerful insights into the universal principles governing the emergence and organizational dynamics of living systems on each and every scale of biological organizational hierarchy, from proteins and cells to economies and ecologies.

Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells

Science.gov (United States)

Korkut, Anil; Wang, Weiqing; Demir, Emek; Aksoy, Bülent Arman; Jing, Xiaohong; Molinelli, Evan J; Babur, Özgün; Bemis, Debra L; Onur Sumer, Selcuk; Solit, David B; Pratilas, Christine A; Sander, Chris

2015-01-01

Resistance to targeted cancer therapies is an important clinical problem. The discovery of anti-resistance drug combinations is challenging as resistance can arise by diverse escape mechanisms. To address this challenge, we improved and applied the experimental-computational perturbation biology method. Using statistical inference, we build network models from high-throughput measurements of molecular and phenotypic responses to combinatorial targeted perturbations. The models are computationally executed to predict the effects of thousands of untested perturbations. In RAF-inhibitor resistant melanoma cells, we measured 143 proteomic/phenotypic entities under 89 perturbation conditions and predicted c-Myc as an effective therapeutic co-target with BRAF or MEK. Experiments using the BET bromodomain inhibitor JQ1 affecting the level of c-Myc protein and protein kinase inhibitors targeting the ERK pathway confirmed the prediction. In conclusion, we propose an anti-cancer strategy of co-targeting a specific upstream alteration and a general downstream point of vulnerability to prevent or overcome resistance to targeted drugs. DOI: http://dx.doi.org/10.7554/eLife.04640.001 PMID:26284497

Günter Blobel: Pioneer of molecular cell biology (1936-2018).

Science.gov (United States)

2018-04-02

Günter Blobel was a scientific colossus who dedicated his career to understanding the mechanisms for protein sorting to membrane organelles. His monumental contributions established research paradigms for major arenas of molecular cell biology. For this work, he received many accolades, including the Nobel Prize in Medicine or Physiology in 1999. He was a scientist of extreme passion and a nurturing mentor for generations of researchers, imbuing them with his deep love of cell biology and galvanizing them to continue his scientific legacy. Günter passed away on February 18, 2018, at the age of 81. © 2018 Rockefeller University Press.

Discovering local patterns of co - evolution: computational aspects and biological examples

Directory of Open Access Journals (Sweden)

Tuller Tamir

2010-01-01

Full Text Available Abstract Background Co-evolution is the process in which two (or more sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn about the functional interdependencies between sets of genes and cellular functions and to predict physical interactions. More generally, it can be used for answering fundamental questions about the evolution of biological systems. Orthologs that exhibit a strong signal of co-evolution in a certain part of the evolutionary tree may show a mild signal of co-evolution in other branches of the tree. The major reasons for this phenomenon are noise in the biological input, genes that gain or lose functions, and the fact that some measures of co-evolution relate to rare events such as positive selection. Previous publications in the field dealt with the problem of finding sets of genes that co-evolved along an entire underlying phylogenetic tree, without considering the fact that often co-evolution is local. Results In this work, we describe a new set of biological problems that are related to finding patterns of local co-evolution. We discuss their computational complexity and design algorithms for solving them. These algorithms outperform other bi-clustering methods as they are designed specifically for solving the set of problems mentioned above. We use our approach to trace the co-evolution of fungal, eukaryotic, and mammalian genes at high resolution across the different parts of the corresponding phylogenetic trees. Specifically, we discover regions in the fungi tree that are enriched with positive evolution. We show that metabolic genes exhibit a remarkable level of co-evolution and different patterns of co-evolution in various biological datasets. In addition, we find that protein complexes that are related to gene expression exhibit non-homogenous levels of co-evolution across different parts of the fungi evolutionary line. In the case of mammalian evolution

Evaluation of the Redesign of an Undergraduate Cell Biology Course

Science.gov (United States)

McEwen, Laura April; Harris, dik; Schmid, Richard F.; Vogel, Jackie; Western, Tamara; Harrison, Paul

2009-01-01

This article offers a case study of the evaluation of a redesigned and redeveloped laboratory-based cell biology course. The course was a compulsory element of the biology program, but the laboratory had become outdated and was inadequately equipped. With the support of a faculty-based teaching improvement project, the teaching team redesigned the…

The Potential of the Cell Processor for Scientific Computing

Energy Technology Data Exchange (ETDEWEB)

Williams, Samuel; Shalf, John; Oliker, Leonid; Husbands, Parry; Kamil, Shoaib; Yelick, Katherine

2005-10-14

The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of the using the forth coming STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. We are the first to present quantitative Cell performance data on scientific kernels and show direct comparisons against leading superscalar (AMD Opteron), VLIW (IntelItanium2), and vector (Cray X1) architectures. Since neither Cell hardware nor cycle-accurate simulators are currently publicly available, we develop both analytical models and simulators to predict kernel performance. Our work also explores the complexity of mapping several important scientific algorithms onto the Cells unique architecture. Additionally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

Effects of space environment on biological characteristics of melanoma B16 cells

International Nuclear Information System (INIS)

Geng Chuanying; Xiang Qing; Xu Mei; Li Hongyan; Xu Bo; Fang Qing; Tang Jingtian; Guo Yupeng

2006-01-01

Objective: To examine the effects of space environment on biological characteristics of melanoma B16 Cells. Methods: B16 cells were carried to the space (in orbit for 8 days, circle the earth 286 times) by the 20th Chinese recoverable satellite, and then harvested and monocloned. 110 strains of space B16 cells were obtained in total. Ten strains of space B16 cells were selected and its morphological changes were examined with the phasecontrast microscope. Flow cytometry and MTT assay were carried out to evaluate the cell cycle and cell viability. Results Morphological changes were observed in the space cells, and melainin granules on the surface in some cells. It was demonstrated by MTF assay that space cells viability varied muti- directionally. It was showed by flow cytometry analysis that G1 phase of space cells was prolonged, S phase shortened. Conclusion: Space environment may change the biological characteristics of melanoma B16 cells. (authors)

Editorial Introduction [to Female Germ Cells: Biology and Genetic Risk

Science.gov (United States)

This is an editorial introduction to the special issue of utation Research, titled, emale Germ Cells: Biology and Genetic isk, which is an attempt to present a collection of papers that emphasize the distinct properties of female germ cells and their characteristic response to mu...

The Emerging Role of PEDF in Stem Cell Biology

Science.gov (United States)

Elahy, Mina; Baindur-Hudson, Swati; Dass, Crispin R.

2012-01-01

Encoded by a single gene, PEDF is a 50 kDa glycoprotein that is highly conserved and is widely expressed among many tissues. Most secreted PEDF deposits within the extracellular matrix, with cell-type-specific functions. While traditionally PEDF is known as a strong antiangiogenic factor, more recently, as this paper highlights, PEDF has been linked with stem cell biology, and there is now accumulating evidence demonstrating the effects of PEDF in a variety of stem cells, mainly in supporting stem cell survival and maintaining multipotency. PMID:22675247

Biology of lung cancer: genetic mutation, epithelial-mesenchymal transition, and cancer stem cells.

Science.gov (United States)

Aoi, Takashi

2016-09-01

At present, most cases of unresectable cancer cannot be cured. Genetic mutations, EMT, and cancer stem cells are three major issues linked to poor prognosis in such cases, all connected by inter- and intra-tumor heterogeneity. Issues on inter-/intra-tumor heterogeneity of genetic mutation could be resolved with recent and future technologies of deep sequencers, whereas, regarding such issues as the "same genome, different epigenome/phenotype", we expect to solve many of these problems in the future through further research in stem cell biology. We herein review and discuss the three major issues in the biology of cancers, especially from the standpoint of stem cell biology.

Transcriptomic signatures shaped by cell proportions shed light on comparative developmental biology

Czech Academy of Sciences Publication Activity Database

Pantalacci, S.; Gueguen, L.; Petit, C.; Lambert, A.; Peterková, Renata; Sémon, E.

2017-01-01

Roč. 18, feb (2017), s. 29 ISSN 1474-760X R&D Projects: GA ČR(CZ) GB14-37368G Institutional support: RVO:68378041 Keywords : comparative transcriptomics * developmental biology * transcriptomic signature Subject RIV: EA - Cell Biology OBOR OECD: Developmental biology Impact factor: 11.908, year: 2016

Computational Modeling in Tissue Engineering

CERN Document Server

2013-01-01

One of the major challenges in tissue engineering is the translation of biological knowledge on complex cell and tissue behavior into a predictive and robust engineering process. Mastering this complexity is an essential step towards clinical applications of tissue engineering. This volume discusses computational modeling tools that allow studying the biological complexity in a more quantitative way. More specifically, computational tools can help in:  (i) quantifying and optimizing the tissue engineering product, e.g. by adapting scaffold design to optimize micro-environmental signals or by adapting selection criteria to improve homogeneity of the selected cell population; (ii) quantifying and optimizing the tissue engineering process, e.g. by adapting bioreactor design to improve quality and quantity of the final product; and (iii) assessing the influence of the in vivo environment on the behavior of the tissue engineering product, e.g. by investigating vascular ingrowth. The book presents examples of each...

Theoretical discussion for quantum computation in biological systems

Science.gov (United States)

Baer, Wolfgang

2010-04-01

Analysis of the brain as a physical system, that has the capacity of generating a display of every day observed experiences and contains some knowledge of the physical reality which stimulates those experiences, suggests the brain executes a self-measurement process described by quantum theory. Assuming physical reality is a universe of interacting self-measurement loops, we present a model of space as a field of cells executing such self-measurement activities. Empty space is the observable associated with the measurement of this field when the mass and charge density defining the material aspect of the cells satisfy the least action principle. Content is the observable associated with the measurement of the quantum wave function ψ interpreted as mass-charge displacements. The illusion of space and its content incorporated into cognitive biological systems is evidence of self-measurement activity that can be associated with quantum operations.

Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories.

Science.gov (United States)

Cardoso, João G R; Jensen, Kristian; Lieven, Christian; Lærke Hansen, Anne Sofie; Galkina, Svetlana; Beber, Moritz; Özdemir, Emre; Herrgård, Markus J; Redestig, Henning; Sonnenschein, Nikolaus

2018-04-20

Computational systems biology methods enable rational design of cell factories on a genome-scale and thus accelerate the engineering of cells for the production of valuable chemicals and proteins. Unfortunately, the majority of these methods' implementations are either not published, rely on proprietary software, or do not provide documented interfaces, which has precluded their mainstream adoption in the field. In this work we present cameo, a platform-independent software that enables in silico design of cell factories and targets both experienced modelers as well as users new to the field. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knockout, knock-in, overexpression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated Web site including documentation, examples, and installation instructions can be found at http://cameo.bio . Users can also give cameo a try at http://try.cameo.bio .

A data integration approach for cell cycle analysis oriented to model simulation in systems biology

Directory of Open Access Journals (Sweden)

Mosca Ettore

2007-08-01

Full Text Available Abstract Background The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to making cancer research more accurate and innovative. In this context the mathematical modelling of the cell cycle has a relevant role to quantify the behaviour of each component of the systems. The mathematical modelling of a biological process such as the cell cycle allows a systemic description that helps to highlight some features such as emergent properties which could be hidden when the analysis is performed only from a reductionism point of view. Moreover, in modelling complex systems, a complete annotation of all the components is equally important to understand the interaction mechanism inside the network: for this reason data integration of the model components has high relevance in systems biology studies. Description In this work, we present a resource, the Cell Cycle Database, intended to support systems biology analysis on the Cell Cycle process, based on two organisms, yeast and mammalian. The database integrates information about genes and proteins involved in the cell cycle process, stores complete models of the interaction networks and allows the mathematical simulation over time of the quantitative behaviour of each component. To accomplish this task, we developed, a web interface for browsing information related to cell cycle genes, proteins and mathematical models. In this framework, we have implemented a pipeline which allows users to deal with the mathematical part of the models, in order to solve, using different variables, the ordinary differential equation systems that describe the biological process. Conclusion This integrated system is freely available in order to support systems biology research on the cell cycle and

Flow velocity-driven differentiation of human mesenchymal stromal cells in silk fibroin scaffolds: A combined experimental and computational approach.

Directory of Open Access Journals (Sweden)

Jolanda Rita Vetsch

Full Text Available Mechanical loading plays a major role in bone remodeling and fracture healing. Mimicking the concept of mechanical loading of bone has been widely studied in bone tissue engineering by perfusion cultures. Nevertheless, there is still debate regarding the in-vitro mechanical stimulation regime. This study aims at investigating the effect of two different flow rates (vlow = 0.001m/s and vhigh = 0.061m/s on the growth of mineralized tissue produced by human mesenchymal stromal cells cultured on 3-D silk fibroin scaffolds. The flow rates applied were chosen to mimic the mechanical environment during early fracture healing or during bone remodeling, respectively. Scaffolds cultured under static conditions served as a control. Time-lapsed micro-computed tomography showed that mineralized extracellular matrix formation was completely inhibited at vlow compared to vhigh and the static group. Biochemical assays and histology confirmed these results and showed enhanced osteogenic differentiation at vhigh whereas the amount of DNA was increased at vlow. The biological response at vlow might correspond to the early stage of fracture healing, where cell proliferation and matrix production is prominent. Visual mapping of shear stresses, simulated by computational fluid dynamics, to 3-D micro-computed tomography data revealed that shear stresses up to 0.39mPa induced a higher DNA amount and shear stresses between 0.55mPa and 24mPa induced osteogenic differentiation. This study demonstrates the feasibility to drive cell behavior of human mesenchymal stromal cells by the flow velocity applied in agreement with mechanical loading mimicking early fracture healing (vlow or bone remodeling (vhigh. These results can be used in the future to tightly control the behavior of human mesenchymal stromal cells towards proliferation or differentiation. Additionally, the combination of experiment and simulation presented is a strong tool to link biological responses to

Computer Simulation and Data Analysis in Molecular Biology and Biophysics An Introduction Using R

CERN Document Server

Bloomfield, Victor

2009-01-01

This book provides an introduction, suitable for advanced undergraduates and beginning graduate students, to two important aspects of molecular biology and biophysics: computer simulation and data analysis. It introduces tools to enable readers to learn and use fundamental methods for constructing quantitative models of biological mechanisms, both deterministic and with some elements of randomness, including complex reaction equilibria and kinetics, population models, and regulation of metabolism and development; to understand how concepts of probability can help in explaining important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data from spectroscopic, genomic, and proteomic sources. These quantitative tools are implemented using the free, open source software program R. R provides an excellent environment for general numerical and statistical computing and graphics, with capabilities similar to Matlab®. Since R is increasingly used in bioinformat...

Using synthetic biology to make cells tomorrow's test tubes.

Science.gov (United States)

Garcia, Hernan G; Brewster, Robert C; Phillips, Rob

2016-04-18

The main tenet of physical biology is that biological phenomena can be subject to the same quantitative and predictive understanding that physics has afforded in the context of inanimate matter. However, the inherent complexity of many of these biological processes often leads to the derivation of complex theoretical descriptions containing a plethora of unknown parameters. Such complex descriptions pose a conceptual challenge to the establishment of a solid basis for predictive biology. In this article, we present various exciting examples of how synthetic biology can be used to simplify biological systems and distill these phenomena down to their essential features as a means to enable their theoretical description. Here, synthetic biology goes beyond previous efforts to engineer nature and becomes a tool to bend nature to understand it. We discuss various recent and classic experiments featuring applications of this synthetic approach to the elucidation of problems ranging from bacteriophage infection, to transcriptional regulation in bacteria and in developing embryos, to evolution. In all of these examples, synthetic biology provides the opportunity to turn cells into the equivalent of a test tube, where biological phenomena can be reconstituted and our theoretical understanding put to test with the same ease that these same phenomena can be studied in the in vitro setting.

Emerging concepts and future challenges in innate lymphoid cell biology

Science.gov (United States)

Artis, David

2016-01-01

Innate lymphoid cells (ILCs) are innate immune cells that are ubiquitously distributed in lymphoid and nonlymphoid tissues and enriched at mucosal and barrier surfaces. Three major ILC subsets are recognized in mice and humans. Each of these subsets interacts with innate and adaptive immune cells and integrates cues from the epithelium, the microbiota, and pathogens to regulate inflammation, immunity, tissue repair, and metabolic homeostasis. Although intense study has elucidated many aspects of ILC development, phenotype, and function, numerous challenges remain in the field of ILC biology. In particular, recent work has highlighted key new questions regarding how these cells communicate with their environment and other cell types during health and disease. This review summarizes new findings in this rapidly developing field that showcase the critical role ILCs play in directing immune responses through their ability to interact with a variety of hematopoietic and nonhematopoietic cells. In addition, we define remaining challenges and emerging questions facing the field. Finally, this review discusses the potential application of basic studies of ILC biology to the development of new treatments for human patients with inflammatory and infectious diseases in which ILCs play a role. PMID:27811053

Dispensing processes impact apparent biological activity as determined by computational and statistical analyses.

Directory of Open Access Journals (Sweden)

Sean Ekins

Full Text Available Dispensing and dilution processes may profoundly influence estimates of biological activity of compounds. Published data show Ephrin type-B receptor 4 IC50 values obtained via tip-based serial dilution and dispensing versus acoustic dispensing with direct dilution differ by orders of magnitude with no correlation or ranking of datasets. We generated computational 3D pharmacophores based on data derived by both acoustic and tip-based transfer. The computed pharmacophores differ significantly depending upon dispensing and dilution methods. The acoustic dispensing-derived pharmacophore correctly identified active compounds in a subsequent test set where the tip-based method failed. Data from acoustic dispensing generates a pharmacophore containing two hydrophobic features, one hydrogen bond donor and one hydrogen bond acceptor. This is consistent with X-ray crystallography studies of ligand-protein interactions and automatically generated pharmacophores derived from this structural data. In contrast, the tip-based data suggest a pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and no hydrophobic features. This pharmacophore is inconsistent with the X-ray crystallographic studies and automatically generated pharmacophores. In short, traditional dispensing processes are another important source of error in high-throughput screening that impacts computational and statistical analyses. These findings have far-reaching implications in biological research.

Computer simulation of induced electric currents and fields in biological bodies by 60 Hz magnetic fields

International Nuclear Information System (INIS)

Xi Weiguo; Stuchly, M.A.; Gandhi, O.P.

1993-01-01

Possible health effects of human exposure to 60 Hz magnetic fields are a subject of increasing concern. An understanding of the coupling of electromagnetic fields to human body tissues is essential for assessment of their biological effects. A method is presented for the computerized simulation of induced electric currents and fields in bodies of men and rodents from power-line frequency magnetic fields. In the impedance method, the body is represented by a 3 dimensional impedance network. The computational model consists of several tens of thousands of cubic numerical cells and thus represented a realistic shape. The modelling for humans is performed with two models, a heterogeneous model based on cross-section anatomy and a homogeneous one using an average tissue conductivity. A summary of computed results of induced electric currents and fields is presented. It is confirmed that induced currents are lower than endangerous current levels for most environmental exposures. However, the induced current density varies greatly, with the maximum being at least 10 times larger than the average. This difference is likely to be greater when more detailed anatomy and morphology are considered. 15 refs., 2 figs., 1 tab

In vitro assessment of a computer-designed potential anticancer agent in cervical cancer cells

Directory of Open Access Journals (Sweden)

Michelle Helen Visagie

Full Text Available BACKGROUND: Computer-based technology is becoming increasingly essential in biological research where drug discovery programs start with the identification of suitable drug targets. 2-Methoxyestradiol (2ME2 is a 17ß-estradiol metabolite that induces apoptosis in various cancer cell lines including cervical cancer, breast cancer and multiple myeloma. Owing to 2ME2's poor in vivo bioavailability, our laboratory in silico-designed and subsequently synthesized a novel 2ME2 analogue, 2-ethyl-3-O-sulphamoyl-estra-1,3,5(10,15-tetraen-17-ol (ESE-15-ol, using receptor- and ligand molecular modeling. In this study, the biological effects of ESE-15-ol (180 nM and its parent molecule, 2ME2 (1 μM, were assessed on morphology and apoptosis induction in cervical cancer cells. RESULTS: Transmission electron microscopy, scanning electron microscopy and polarization-optical transmitted light differential interference contrast (PlasDIC images demonstrated morphological hallmarks of apoptosis including apoptotic bodies, shrunken cells, vacuoles, reduced cell density and cell debris. Flow cytometry analysis showed apoptosis induction by means of annexin V-FITC staining. Cell cycle analysis showed that ESE-15-ol exposure resulted in a statistically significant increase in the G2M phase (72% compared to 2ME2 (19%. Apoptosis induction was more pronounced when cells were exposed to ESE-15-ol compared to 2ME2. Spectrophotometric analysis of caspase 8 activity demonstrated that 2ME2 and ESE-15-ol both induced caspase 8 activation by 2- and 1.7-fold respectively indicating the induction of the apoptosis. However, ESE-15-ol exerted all of the above-mentioned effects at a much lower pharmacological concentration (180 nM compared to 2ME2 (1 μM physiological concentration. CONCLUSION: Computer-based technology is essential in drug discovery and together with in vitro studies for the evaluation of these in silico-designed compounds, drug development can be improved to be

What it takes to understand and cure a living system: computational systems biology and a systems biology-driven pharmacokinetics-pharmacodynamics platform

NARCIS (Netherlands)

Swat, Maciej; Kiełbasa, Szymon M.; Polak, Sebastian; Olivier, Brett; Bruggeman, Frank J.; Tulloch, Mark Quinton; Snoep, Jacky L.; Verhoeven, Arthur J.; Westerhoff, Hans V.

2011-01-01

The utility of model repositories is discussed in the context of systems biology (SB). It is shown how such repositories, and in particular their live versions, can be used for computational SB: we calculate the robustness of the yeast glycolytic network with respect to perturbations of one of its

SYSTEMS BIOLOGY AND METABOLIC ENGINEERING OF ARTHROSPIRA CELL FACTORIES

Directory of Open Access Journals (Sweden)

Amornpan Klanchui

2012-10-01

Full Text Available Arthrospira are attractive candidates to serve as cell factories for production of many valuable compounds useful for food, feed, fuel and pharmaceutical industries. In connection with the development of sustainable bioprocessing, it is a challenge to design and develop efficient Arthrospira cell factories which can certify effective conversion from the raw materials (i.e. CO2 and sun light into desired products. With the current availability of the genome sequences and metabolic models of Arthrospira, the development of Arthrospira factories can now be accelerated by means of systems biology and the metabolic engineering approach. Here, we review recent research involving the use of Arthrospira cell factories for industrial applications, as well as the exploitation of systems biology and the metabolic engineering approach for studying Arthrospira. The current status of genomics and proteomics through the development of the genome-scale metabolic model of Arthrospira, as well as the use of mathematical modeling to simulate the phenotypes resulting from the different metabolic engineering strategies are discussed. At the end, the perspective and future direction on Arthrospira cell factories for industrial biotechnology are presented.

Thematic minireview series: cell biology of G protein signaling.

Science.gov (United States)

Dohlman, Henrik G

2015-03-13

This thematic series is on the topic of cell signaling from a cell biology perspective, with a particular focus on G proteins. G protein-coupled receptors (GPCRs, also known as seven-transmembrane receptors) are typically found at the cell surface. Upon agonist binding, these receptors will activate a GTP-binding G protein at the cytoplasmic face of the plasma membrane. Additionally, there is growing evidence that G proteins can also be activated by non-receptor binding partners, and they can signal from non-plasma membrane compartments. The production of second messengers at multiple, spatially distinct locations represents a type of signal encoding that has been largely neglected. The first minireview in the series describes biosensors that are being used to monitor G protein signaling events in live cells. The second describes the implementation of antibody-based biosensors to dissect endosome signaling by G proteins and their receptors. The third describes the function of a non-receptor, cytoplasmic activator of G protein signaling, called GIV (Girdin). Collectively, the advances described in these articles provide a deeper understanding and emerging opportunities for new pharmacology. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Agent-Based Modeling in Molecular Systems Biology.

Science.gov (United States)

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-06-08

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

Autotaxin: Its Role in Biology of Melanoma Cells and as a Pharmacological Target

Directory of Open Access Journals (Sweden)

Maciej Jankowski

2011-01-01

Full Text Available Autotaxin (ATX is an extracellular lysophospholipase D (lysoPLD released from normal cells and cancer cells. Activity of ATX is detected in various biological fluids. The lysophosphatidic acid (LPA is the main product of ATX. LPA acting through specific G protein-coupled receptors (LPA1-LPA6 affects immunological response, normal development, and malignant tumors' formation and progression. In this review, the impact of autotoxin on biology of melanoma cells and potential treatment is discussed.

Complex fluids in biological systems experiment, theory, and computation

CERN Document Server

2015-01-01

This book serves as an introduction to the continuum mechanics and mathematical modeling of complex fluids in living systems. The form and function of living systems are intimately tied to the nature of surrounding fluid environments, which commonly exhibit nonlinear and history dependent responses to forces and displacements. With ever-increasing capabilities in the visualization and manipulation of biological systems, research on the fundamental phenomena, models, measurements, and analysis of complex fluids has taken a number of exciting directions. In this book, many of the world’s foremost experts explore key topics such as: Macro- and micro-rheological techniques for measuring the material properties of complex biofluids and the subtleties of data interpretation Experimental observations and rheology of complex biological materials, including mucus, cell membranes, the cytoskeleton, and blood The motility of microorganisms in complex fluids and the dynamics of active suspensions Challenges and solut...

Biology and clinical application of CAR T cells for B cell malignancies.

Science.gov (United States)

Davila, Marco L; Sadelain, Michel

2016-07-01

Chimeric antigen receptor (CAR)-modified T cells have generated broad interest in oncology following a series of dramatic clinical successes in patients with chemorefractory B cell malignancies. CAR therapy now appears to be on the cusp of regulatory approval as a cell-based immunotherapy. We review here the T cell biology and cell engineering research that led to the development of second generation CARs, the selection of CD19 as a CAR target, and the preclinical studies in animal models that laid the foundation for clinical trials targeting CD19+ malignancies. We further summarize the status of CD19 CAR clinical therapy for non-Hodgkin lymphoma and B cell acute lymphoblastic leukemia, including their efficacy, toxicities (cytokine release syndrome, neurotoxicity and B cell aplasia) and current management in humans. We conclude with an overview of recent pre-clinical advances in CAR design that argues favorably for the advancement of CAR therapy to tackle other hematological malignancies as well as solid tumors.

Dynamic cell culture system: a new cell cultivation instrument for biological experiments in space

Science.gov (United States)

Gmunder, F. K.; Nordau, C. G.; Tschopp, A.; Huber, B.; Cogoli, A.

1988-01-01

The prototype of a miniaturized cell cultivation instrument for animal cell culture experiments aboard Spacelab is presented (Dynamic cell culture system: DCCS). The cell chamber is completely filled and has a working volume of 200 microliters. Medium exchange is achieved with a self-powered osmotic pump (flowrate 1 microliter h-1). The reservoir volume of culture medium is 230 microliters. The system is neither mechanically stirred nor equipped with sensors. Hamster kidney (Hak) cells growing on Cytodex 3 microcarriers were used to test the biological performance of the DCCS. Growth characteristics in the DCCS, as judged by maximal cell density, glucose consumption, lactic acid secretion and pH, were similar to those in cell culture tubes.

Nanoscopical dissection of ancestral nucleoli in Archaea: a case of study in Evolutionary Cell Biology

KAUST Repository

Islas Morales, Parsifal

2018-01-01

Evolutionary cell biology (ECB) has raised increasing attention in the last decades. Is this a new discipline and an historical opportunity to combine functional and evolutionary biology towards the insight that cell

Teaching Cell and Molecular Biology for Gender Equity

Science.gov (United States)

Sible, Jill C.; Wilhelm, Dayna E.; Lederman, Muriel

2006-01-01

Science, technology, engineering, and math (STEM) fields, including cell biology, are characterized by the "leaky pipeline" syndrome in which, over time, women leave the discipline. The pipeline itself and the pond into which it empties may not be neutral. Explicating invisible norms, attitudes, and practices by integrating social…

Tip cell overtaking occurs as a side effect of sprouting in computational models of angiogenesis.

Science.gov (United States)

Boas, Sonja E M; Merks, Roeland M H

2015-11-21

During angiogenesis, the formation of new blood vessels from existing ones, endothelial cells differentiate into tip and stalk cells, after which one tip cell leads the sprout. More recently, this picture has changed. It has become clear that endothelial cells compete for the tip position during angiogenesis: a phenomenon named tip cell overtaking. The biological function of tip cell overtaking is not yet known. From experimental observations, it is unclear to what extent tip cell overtaking is a side effect of sprouting or to what extent it is regulated through a VEGF-Dll4-Notch signaling network and thus might have a biological function. To address this question, we studied tip cell overtaking in computational models of angiogenic sprouting in absence and in presence of VEGF-Dll4-Notch signaling. We looked for tip cell overtaking in two existing Cellular Potts models of angiogenesis. In these simulation models angiogenic sprouting-like behavior emerges from a small set of plausible cell behaviors. In the first model, cells aggregate through contact-inhibited chemotaxis. In the second model the endothelial cells assume an elongated shape and aggregate through (non-inhibited) chemotaxis. In both these sprouting models the endothelial cells spontaneously migrate forwards and backwards within sprouts, suggesting that tip cell overtaking might occur as a side effect of sprouting. In accordance with other experimental observations, in our simulations the cells' tendency to occupy the tip position can be regulated when two cell lines with different levels of Vegfr2 expression are contributing to sprouting (mosaic sprouting assay), where cell behavior is regulated by a simple VEGF-Dll4-Notch signaling network. Our modeling results suggest that tip cell overtaking can occur spontaneously due to the stochastic motion of cells during sprouting. Thus, tip cell overtaking and sprouting dynamics may be interdependent and should be studied and interpreted in combination. VEGF

An overview of bioinformatics methods for modeling biological pathways in yeast.

Science.gov (United States)

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin

2016-03-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Neural crest cells: from developmental biology to clinical interventions.

Science.gov (United States)

Noisa, Parinya; Raivio, Taneli

2014-09-01

Neural crest cells are multipotent cells, which are specified in embryonic ectoderm in the border of neural plate and epiderm during early development by interconnection of extrinsic stimuli and intrinsic factors. Neural crest cells are capable of differentiating into various somatic cell types, including melanocytes, craniofacial cartilage and bone, smooth muscle, and peripheral nervous cells, which supports their promise for cell therapy. In this work, we provide a comprehensive review of wide aspects of neural crest cells from their developmental biology to applicability in medical research. We provide a simplified model of neural crest cell development and highlight the key external stimuli and intrinsic regulators that determine the neural crest cell fate. Defects of neural crest cell development leading to several human disorders are also mentioned, with the emphasis of using human induced pluripotent stem cells to model neurocristopathic syndromes. © 2014 Wiley Periodicals, Inc.

Complex network problems in physics, computer science and biology

Science.gov (United States)

Cojocaru, Radu Ionut

There is a close relation between physics and mathematics and the exchange of ideas between these two sciences are well established. However until few years ago there was no such a close relation between physics and computer science. Even more, only recently biologists started to use methods and tools from statistical physics in order to study the behavior of complex system. In this thesis we concentrate on applying and analyzing several methods borrowed from computer science to biology and also we use methods from statistical physics in solving hard problems from computer science. In recent years physicists have been interested in studying the behavior of complex networks. Physics is an experimental science in which theoretical predictions are compared to experiments. In this definition, the term prediction plays a very important role: although the system is complex, it is still possible to get predictions for its behavior, but these predictions are of a probabilistic nature. Spin glasses, lattice gases or the Potts model are a few examples of complex systems in physics. Spin glasses and many frustrated antiferromagnets map exactly to computer science problems in the NP-hard class defined in Chapter 1. In Chapter 1 we discuss a common result from artificial intelligence (AI) which shows that there are some problems which are NP-complete, with the implication that these problems are difficult to solve. We introduce a few well known hard problems from computer science (Satisfiability, Coloring, Vertex Cover together with Maximum Independent Set and Number Partitioning) and then discuss their mapping to problems from physics. In Chapter 2 we provide a short review of combinatorial optimization algorithms and their applications to ground state problems in disordered systems. We discuss the cavity method initially developed for studying the Sherrington-Kirkpatrick model of spin glasses. We extend this model to the study of a specific case of spin glass on the Bethe

Relationship between α/β and radiosensitivity and biologic effect of fractional irradiation of tumor cells

International Nuclear Information System (INIS)

Guo Chuanling; Chinese Academy of Sciences, Beijing; Wang Jufang; Jin Xiaodong; Li Wenjian

2006-01-01

Five kinds of malignant human tumor cells, i.e. SMMC-7721, HeLa, A549, HT29 and PC3 cell lines, were irradiated by 60 Co γ-rays to 1-6 Gy in a single irradiation or two irradiations of half dose. The radiosensitivity was compared with the dose-survival curves and D 50 and D 10 values. Differences in the D 50 and D 10 between the single and fractional irradiation groups showed the effect of fractional irradiation. Except for PC3 cells, all the cell lines showed obvious relationship between radiosensitivity and biologic effect of fractional irradiation and the α/β value. A cell line with bigger α/β was more radiation sensitive, with less obvious effect of fractional irradiation. The results indicate that there were obvious differences in radiosensitivity, repair ability and biologic effect of fractional irradiation between tumor cells from different tissues. To some tumor cell lines, the relationship between radiosensitivity, biologic effect of fractional irradiation and repair ability was attested. The α/β value of single irradiation can be regarded as a parameter to investigate the radiosensitivity and biologic effect of fractional irradiation of tumor cells. (authors)

Mycoplasma testing of cell substrates and biologics: Review of alternative non-microbiological techniques.

Science.gov (United States)

Volokhov, Dmitriy V; Graham, Laurie J; Brorson, Kurt A; Chizhikov, Vladimir E

2011-01-01

Mycoplasmas, particularly species of the genera Mycoplasma and Acholeplasma, are known to be occasional microbial contaminants of cell cultures that produce biologics. This presents a serious concern regarding the risk of mycoplasma contamination for research laboratories and commercial facilities developing and manufacturing cell-derived biological and biopharmaceutical products for therapeutic use. Potential undetected contamination of these products or process intermediates with mycoplasmas represents a potential safety risk for patients and a business risk for producers of biopharmaceuticals. To minimize these risks, monitoring for adventitious agents, such as viruses and mycoplasmas, is performed during the manufacture of biologics produced in cell culture substrates. The "gold standard" microbiological assay, currently recommended by the USP, EP, JP and the US FDA, for the mycoplasma testing of biologics, involves the culture of viable mycoplasmas in broth, agar plates and indicator cells. Although the procedure enables highly efficient mycoplasma detection in cell substrates and cell-derived products, the overall testing strategy is time consuming (a minimum of 28 days) and requires skilled interpretation of the results. The long time period required for these conventional assays does not permit their use for products with short shelf-lives or for timely 'go/no-go' decisions during routine in-process testing. PCR methodology has existed for decades, however PCR based and other alternative methods for mycoplasma detection have only recently been considered for application to biologics manufacture. The application of alternative nucleic acid-based, enzyme-based and/or recombinant cell-culture methods, particularly in combination with efficient sample preparation procedures, could provide advantages over conventional microbiological methods in terms of analytical throughput, simplicity, and turnaround time. However, a challenge to the application of alternative

Cell-free protein synthesis enabled rapid prototyping for metabolic engineering and synthetic biology

Directory of Open Access Journals (Sweden)

Lihong Jiang

2018-06-01

Full Text Available Advances in metabolic engineering and synthetic biology have facilitated the manufacturing of many valuable-added compounds and commodity chemicals using microbial cell factories in the past decade. However, due to complexity of cellular metabolism, the optimization of metabolic pathways for maximal production represents a grand challenge and an unavoidable barrier for metabolic engineering. Recently, cell-free protein synthesis system (CFPS has been emerging as an enabling alternative to address challenges in biomanufacturing. This review summarizes the recent progresses of CFPS in rapid prototyping of biosynthetic pathways and genetic circuits (biosensors to speed up design-build-test (DBT cycles of metabolic engineering and synthetic biology. Keywords: Cell-free protein synthesis, Metabolic pathway optimization, Genetic circuits, Metabolic engineering, Synthetic biology

Micrasterias as a model system in plant cell biology

Directory of Open Access Journals (Sweden)

Ursula Luetz-Meindl

2016-07-01

Full Text Available The unicellular freshwater alga Micrasterias denticulata is an exceptional organism due to its extraordinary star-shaped, highly symmetric morphology and has thus attracted the interest of researchers for many decades. As a member of the Streptophyta, Micrasterias is not only genetically closely related to higher land plants but shares common features with them in many physiological and cell biological aspects. These facts, together with its considerable cell size of about 200 µm, its modest cultivation conditions and the uncomplicated accessibility particularly to any microscopic techniques, make Micrasterias a very well suited cell biological plant model system. The review focuses particularly on cell wall formation and composition, dictyosomal structure and function, cytoskeleton control of growth and morphogenesis as well as on ionic regulation and signal transduction. It has been also shown in the recent years that Micrasterias is a highly sensitive indicator for environmental stress impact such as heavy metals, high salinity, oxidative stress or starvation. Stress induced organelle degradation, autophagy, adaption and detoxification mechanisms have moved in the center of interest and have been investigated with modern microscopic techniques such as 3-D- and analytical electron microscopy as well as with biochemical, physiological and molecular approaches. This review is intended to summarize and discuss the most important results obtained in Micrasterias in the last 20 years and to compare the results to similar processes in higher plant cells.

G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.

Science.gov (United States)

Lee, Hui Sun; Im, Wonpil

2016-04-01

Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. © 2016 The Protein Society.